{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# Plot multinomial and One-vs-Rest Logistic Regression\n",
    "# 多项式与One-vs-Rest的Logistic回归的决策面展示\n",
    "\n",
    "Plot decision surface of multinomial and One-vs-Rest Logistic Regression. The hyperplanes corresponding to the three One-vs-Rest (OVR) classifiers are represented by the dashed lines.\n",
    "  \n",
    "绘制多项式与OVR的Logisitc回归的决策面，其中三个One-vs-Rest(OVR)分类器的超平面用虚线表示。\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Automatically created module for IPython interactive environment\n"
     ]
    }
   ],
   "source": [
    "print(__doc__)\n",
    "# Authors: Tom Dupre la Tour <tom.dupre-la-tour@m4x.org>\n",
    "# License: BSD 3 clause\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.datasets import make_blobs\n",
    "from sklearn.linear_model import LogisticRegression"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## sklearn.datasets.make_blobs聚类数据生成器\n",
    "sklearn.datasets.make_blobs(n_samples=100, n_features=2,centers=3, cluster_std=1.0, center_box=(-10.0, 10.0), shuffle=True, random_state=None)  \n",
    "- n_samples：表示数据样本点个数,默认值100\n",
    "- n_features：表示数据的维度，每个样本的特征数，默认值是2\n",
    "- centers：产生数据的中心点（即类别数），默认值3\n",
    "- cluster_std：数据集的标准差，浮点数或者浮点数序列，默认值1.0，例如我们希望生成2类数据，其中一类比另一类具有更大的方差，可以将cluster_std设置为[1.0,3.0]\n",
    "- center_box：中心确定之后的数据边界，默认值(-10.0, 10.0)\n",
    "- shuffle ：洗乱，默认值是True\n",
    "- random_state:官网解释是随机生成器的种子"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make 3-class dataset for classification\n",
    "# 创建3分类数据集的中心点\n",
    "centers = [[-5, 0], [0, 1.5], [5, -1]]\n",
    "# 生成数据\n",
    "X, y = make_blobs(n_samples=1000, centers=centers, random_state=40)\n",
    "\n",
    "# 对X进行矩阵变换\n",
    "transformation = [[0.4, 0.2], [-0.4, 1.2]]\n",
    "X = np.dot(X, transformation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "训练模型的性能: 0.995 (multinomial)\n",
      "训练模型的性能: 0.976 (ovr)\n"
     ]
    },
    {
     "data": {
      "image/png": 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eigkTPRLdeudpqOjJce4nxazij7H/x2PV1/Nfx7CuHk7YkLQmnogKM3mWCROdgR5B7NCz49znJN9DpqWY7xwju3ooYYNGU3mCnepjTCeqCRPhRpdkd+wsrHl3bY/MCpliqWBV5jjiLR0nwVKXi10uF7lWK2nWrrOYFYqKk+zoKE3Ct3FdNg4TJnoieozF7kFP1dw9pL62fjQ/Ow9tVx8rauyMKyrkztISxhUVsqLGHs4hthmJa2Nx9HfiyHF26ThMmOhp6HHEDj2X3Gt1DDeUP8rNtgdx6rY9bJW6XMy22ViNZp3WrEYz22aj1NV1IYcJX8eBG6p6YMZHEya6Ej2S2KFnknusqmNu8mw2On/HsupJbTp2l8tFfwXDjf+HA/2UvN5ViKiwEvu/aKqPre1xGR9NmOhK9Fhih55J7mfEfsDZMe+wuGoavzoPCfm4XKuVHRo2GP9vAHZqeb0rkbA2Dkudwp2w/+aOyb/kDTMnu4luhR5N7LB/kXupy8V6h6NVeWRu8mwSLNXcYltEgw6NmNOsVuampJCHYoRS5KGYm5LSpQ5UgKTVceTO7o212gx9NGEiXOhRUTHBsD9Ey6yosTPbZqO/gh0a5qakMD6uWZJMANKsZdyXPJNCVxYWQrd0x8fFMyY6pltExXjgSeXrjnajHAqlzVztJkx0FD3eYvegO1vu7XFsnhn7PlcmPIdFtU2bTrNaGREV1S1I3YPaQ+rZ9lgBdUMcXT0UEyZ6BA4YYofuS+4dcWy+V3sml5c+h0vvv7cyekckKKgabUbHmDARDuy/bNBOdEdy74hj06Gj+KT+FJ6x/61Tx9iZsNRbiP8hhupRtWirGR1jwkRHccARO3Q/cu+IY/O82Lc4NeYjFlbextaGg/bBaDsHCWvjcCe5qTm8vquHYsLEfo8Dktih+5H7+Lh4VvXOYm5aBqt6ZwV1nPpDKbgveSYxqo7ptgdw76fOx/gfY7DYFdXmZiUTJjqMA5bYofuRe3sdm72txcxJvof/OI5hdX1e5wyuk6EaFJlPp5KyMrGrh2LCxH6PA5rYofuRe3vxx9jXeT3tQk6KWdXuPkKNo+8sJHwbR/SuyC45twkTPQkHPLHDvif3ziBQpWBU9LcAbG/o32ZJpi0JwkIdf3uus2ZoHbZTq0Nub8KEieYwid3AviL3zs6w+LPzUE4u/oTlNZeFfExb4uhDHX+o7fzJ335MLaUX23DH7L8pBkyY6GqYxO6Fzib3fZFh8dCIXxgV/Q3zK2exq6FvSMeEGkcf6vhDbReI/BPWxqGjwH60WQ/VhIn2wiR2P3Qmue+LDItKwT+Sb0Whuc22EB1CWHiocfShjj+UdsHI3/6LlYi9VqqONYndhIn2wiT2AOgsct9XGRb7ROQzO2kuXziO55Wai1ttH2ocfajjD6XdLpeLPmgf8s9Bs7vBTcLXsdT8rg5XQtelFDZhYn+GSexB0Bnkvi8zLF4S9zLHR39OiTsjpPahxNGHOv5Q2sUr2IIv+W81Xk/8Kg5rpQVHVkP7Lr4LMHPLvV09BBMmGnFAZHdsLzojK+S+yrCoFCzvdRlWFboTMi2E8YQ6/tba2TX0BsYB/YEdQKbxetSOSAZMzTYzPZow0U6YxN4KOoPcQyHQYGhLMWoPqa+tH02Zuxdnxa5s1zn9Eer4W2qXa7VSgeLfaOIBO3ABilyrVVL5atBKoyPA4jQJ3oSJtsCUYkJAd9nE1J5QSa3hoaqbuM22kAJXVrP3O2tTUmv9euSaC1BcrRQX+Mk1rng32x8poPJkM6bdhIm2wiT2ENHV5N7eUEml4P6UGTiIYqbtPp8omc6KqX+luooTiwqY3Uq/Len6VruFCJvVLHRtwkQ7YBJ7G9CV5N6RUMmDIrYzI/F+Pqk/hX/XXgB0Xkz9y9VV3F1ZwefA+hD6DZQfx2PtW76Mof5gJ87M/ceJasJEd0DYiF0pZVVKrVNKvRuuPrsjuorcOxoqeUX8c4yM/A9zKu6hxJXeKTH1pS4X8yorOATffnPb0K/3U8Rl71QBZgEOEybainBa7NOAn8PYX7fFui+n7vNzdjRU0qrcPJA6nesSHmBXQwHxRm1V74Viu9bEd8BPucvloj+wC99+d2gd0gLk/xTxejH8/F+wmXKMCRNtQliiYpRSfYGzgHnAzeHoszujunwCa96dsM8LZHc0VPInx395smoNHyrYri1cEBtLXm0tOWi2IuGHF5aUtFhIuyXkWq3sQXE7mnFAX2ATcHdSckhjbXyKMPwAw4G/Pw8DUuLR6MbC1yZMmGgZ4bLYHwZuA4IGTSulrlFKfaeU+q6qvCxMp+1adJXl3p6c7d7W8Hx9Gsn8xBu1CTyTlsZOYCWwDdqltZe6XHxWV8tGp5Pbk5JYgCLb6G9OUjIXJzTPsR4oaiaQ3PTJD4qcn+JMUjdhog3osMWulDobKNZaf6+UygvWTmv9JPAkwMDDhveIwpZdZbm3B97WcAQ7KGAAMTzKf51XM0gp8oxwGW+tPZTFY0WNnZm2cjKBfEABdyYlc3hUdMCnilKXi6erK1lutzNAKXZqGp8QGuUmm41+isb3Evu6KTvGTurbiSbBmzARAsJhsY8BxiultgP/BE5SSr0Uhn73G3R1KGQo8LaGD+NnrmMOlfyJ+ytPYZPWITllva1sj5U+y1bOGkRyWQtEAfdVVgQk9RU1dsYWFfCs3R40aiZQCGTdYAdlF1VSP9DZafNjwkRPQoeJXWs9U2vdV2s9APgL8KnW+tIOj2w/Q3cn9ybnKxwMvMgDDOQ/RPMYijROgBadst7RKmOLCjihqICFZWU4afKYDwcGIKkBAqf8LecJ4FCaomaygTQ0G51NpO0vN8V/FwtOqDrOdKKaMBEKzDj2MKK7k/v4uHge6ZWOFfgNF29zBdWkkMxfWNorLWgCMG99/iOtiQTWAD+iWQtMAkowImuAQqDC7fLRz3e5XOSiONVoswF4DRhivD+lbG/QjUzWGgvxP8ZQPboGrTpXxevq8oAmTIQDYSV2rfVqrfXZ4exzf0N3J/dhkZGUoCgAhvETb3A4NTzGsMgocq1WdrlczUjNO+Z9O3AQvnHqvYAjgWMBj039j/Iyn12nuVYru9AUAI8BJwBXAqsRGWc1tOi0TVgbhyvVTe2h9WGZh0Do7OpWJkzsK5gWeyegO5O7fzz8RLYwNyWF/6sZwIlFjoCk5q3PD0CiXbw1+QLABoyKjMQCfEFz/VzOm8rxwB1AHSLD+G9k+qSuLmBFpi3fWFE2C87enWNJ74vqViZM7CuYxN5J6IpQyFDh76A8PDKbeVUfMZaHApJamtXKjKQkxiJpdh3A8YhWnwc8C3wFfOV0MpjmZL3R6WC9w8GY6Bg+753NPb3SeCilF2X4LhCbtOa5inLGFRXycnUV6x0OXq6uEis6fy8XXujms/AkqGyGcOzEPfua0zplbCZMtBVm2t5OQncPhfROqbvLtZfePMh73MW7vMbZvOcT8riixs79lZUMVIrtWnNXUjJ9IiK5t2wvvwKeUh45wE6EpIcbv7dpzeSyUg5Sih1eoY0AGk2erZw+SNGNu5HNEAvR3F1ZwWCl2KQ104FzNOzR8FdbOUNjIxisosM6H95PJZ6xd0Z1KxMm9gVMi72Tcd78lK4eQqvItVqpZx6D2cC1PMEXJLNTayrcbjY5HY0SxXqteQuYW1lBnKJRqwchwkJgCmLVHwGMRnasfQ5B5Q034Klu2h9xwt4PfA38qDVfAw8AfwIuBv7xIHx2eUnY9e99Wd3KhInOhknsnYxbhr/frWUZEFKblxJPIVeST29O4kEcwAPlpZxbUtxYm/Q14EJEG7+idC/nx8Y2EuEJwCnR0Swx3t8G/C0+nsFKBZQ3PJr258BmhMgnAeuAXHwlkYOBcqPNifmQNxburSkPu/4dSnlAEyb2B5jEvg9QXT6hW1nugUL6xsfFs6Z3PufFPIyFYr5ErOwViEyyGrgeWAX8iljhb9bW8EZGBscbBLjT4cACnJWQyJre2VyVkNQob5QAryCJxnKtVjY6naSjyTbO74mumQj8hq/2vgux5ocDvT8F4uC0YzuWiTIY2puywYSJ7gST2PcRbhn+freIlmkppC/NauVvCf9gqJrFEcZrRYhccjqQRvMwxwUVFTxjr/baSQpPVVc39jc3JYUxSDTNHEADSyormFK2F43Esb9GE/nHAn+LTyAPxRFKMRqRd/YYbVLWgyqFQ8eZ+rcJE8FgEvs+RleSeyghfR4n4lOM41bmMAn4FpFIivC1pMuAzx31DETkl/8Yv73zr4+JjiESSTewCdnY9GptDf+mKX79SuA4oMHo86qERFb1zmJeWgZzkpJ5FEUiotn/zg3vrIZRx0Jqgpk3xoSJQDCjYroAnVEgOxQESovrn/DLY2VPsZ1BPbeSwxcM5xMAZiCbkIYAO4BlwJ2Inj4E2bi0Daj3yr8u51QM90oy1hfwqNfDkcWgFomFPzE62mcsI6KiOD02jo1OJ5VuF0kWC0PXKmJKXNBgErsJE4FgWuxdhK5wqIZahWl8XDyfZS4jy7KZQp5hLQmAWNVuYDrwCzAU2I18iFYD3xu/rcBX9fV8VlcbsKDHbsDu9X8ZsB6x6lfV1zdzin5ZX8eUslKerLAxpayMr7e4SFoTj8VpErsJE4FgEnsXQeLc960s05aQvj4RTpb1mo4ml3EsZIRSXIDi4tg4bkBxqnH8qdHRZOGrvccD021l3F1WynklxT7RM3kojoqI5Ezgd8gTwDIkFn44kkDsqerKxnEElo/KWRNZw54/VOJKNHeGthcVdQ1sKq2los6sKdvTYEoxXYx1X07lyDFL9tn5Qq3CVOpyEcFaLol7ipdqJvHXpLc5OWYDaVYrU5Nc7HK5iFeQ73Ixub6eDYik8gYiqXxD00afE2preC4tnUhlIV5JlabpwIOIM3WocU5PeoJn7XYujItncGRUQPmoF/CUtYy7JsJXtQ0cv6ZXZ01Xj8WanRU8sa6Q3hmKohLNtSOyOL5/clcPy0SYYBJ7J6KyvJSS/F1k5OSSlJoWsE11+QTWfck+Jfe0FggdJHJmts1GfwXb9c1cEruRcdH/bXSIplmtfFlf19hGA6OQx79s4/fPCAkPR6zxiaV7WZCSSr+ISPqgOQc4DTgZSU8wENiKOFD7A+eXFDM/JZWhkZFsM/LFexaKMuCrrfDLdig7tobS1aGV3jMhqKhr4Il1hTy0RDNokGbLFrhpaiHDe8eTHGNSQk+AeRc7CV+9v4In752NNbI/LucOrpkzl+NOHx+wbVeQeyCUulxsdDqZbStnNWIlb6CG42sf5d1a6Ec8u6lhRlIS91dWshrNcC26+pmIRu4h3zzgJMQCLwNWABfYbNyQmMAW4GrE0aoQC/xnRL//zquP423lKCAViYjpi6QseASRbGo+hYbL4X+JdSTaIttVB/ZARLHdSe8MxaBB8hg0aBD0zlAU250msfcQmBp7J6CyvJQn752No341tdXrcNSv5sl7ZlNZXhr0mK7exOSJb7+3bG+zePUM4GaOIZ/tPMgY5lVWkOuVMCue5rtFPal8T0DS9OYB2WgWV1XxNeIsXYPErX9r/ESCz4alDOPYbYjDdrdxnhlI7Hv5p2CxwIdHlpupdtuAzPhIikrEUgfYsgWKSjSZ8ZFdOzATYYNJ7J2AkvxdWCM9eyUBhmON6EdJ/q4Wj+uq9APeDsovgFKap+W9jJ9IopJ5PEsWsT7l9OzI7lDvY0qQNABvIZb7K0jqgN74LgADkBzvnrDHj433ViNEfqTR11IkpYB37PuJe+C3n+HanOC5aHoSwuXsTI6J4NoRWdw0VXH15RZumqq4dkSWaa33IJh3shOQkZOLy7kD71yBroadZOTktnpsV2SF9HdQLkOiVQah2I1GATuwcyt/43pWEcHfmcl0xiHyyCZEG/fIJbuBCbFxHB0dzTm2ctwIaUcBxQgxxyO7STcDCchM5QPXATMRMu+LFNSdBPTBd0EYCBwXH88T0+x872x6vS2FuMON/Eve4MNBd3Fa3wfD3ne4nZ3H909meO94iu1OMo+K7DCpV9Q1SF/xHe/LRMdh3oFOQFJqGtfMmcuT9+RhjeiHq2En18yZG9SBGgj7chOTf8qGvo6lAAAgAElEQVTaoUgs+qSUFI6LjmFJZQVn1taQy2qsLKOBmzidN5jCWrYDf0XI/B0kV/tW4NbaGi5NSCASIXKPbn4MosenINEzOcBIZGHQxs9exDr3WPBXGuPxdqBuARrsdjzL5zArbHT1zFS7gZyd06YUkBBlZWBqTLuJNDkmIiwkbEbYdD+YxN5JOO708QwbNabVqJiWsK9CIRvj2202ctBsRSSTO2w2ZiQl8WZtLV8jpLqW2xjDmSzlbF5mLQWIBt4XSTlwPSKvuIFlVVU+u04jEe1vJZIl0tPnBsTafwVZJA5GwiWnIxEyVuAcRKfvhVj2d+PJ3Q5PXAPHHQNTrqIxLr/U5WoW0hnotbago8e3F/7Ozh07wOWGF7fuoWQvXUqkZoRN94Q5852IpNS0dhG6B/tSlhkfF8/QyEjOLSlmJUKiG9CMraxgoFKNMs2xVHMIR/EOZRyMyCmnAR8hkslqvKJa6mpRxt/ZwAKa0gkMwFda6Yvo9BnIrtZpwCHGa3OA+4B3keyP2QipY/y+rhD6DIJlRyZzaH6MT7imp7gH0Oy1tqTlDdRnZ6f19cgbMRGWRmdnWho89BA8upRuQaRmhE33hDnz+wHOm5/CW7NsnX4eu4ZBSpHnldelH5Jq11sGKaactzMymV6ezZ4G2MmPaMSa9o+mOSw6mjH19TiR0EaFOFu34yut7AZmAzHG8d7W/Dgk5NFTeC6CpsXiY2DFZ/CnqfDj0RVcu66CBqRU33BDXjrBVt6Y9sDzWp7NxpjomJAsb2/ncnuObw/W7Kxg2Q8FpCYryis043KTuWlqJclJkJysGTRI2nU1kXpH2Awa5BVhc5QZYdOVMKNi9gOEI1rGOwd7oHzsEDiXTD6KWUnJzdIQJKtI1je8Tg4v8zVRfIBIJJ5jVyOO0k/r67EAcYi8cjWisUch8svBNFVaehspcu1fN7Wv0XeE0W5mUnJjKuDZgK0CYr6H8SfBZ0Yb/zzvaX6vtaWeaTjqobYFFXUNLP2uAGWF2ESNssInOyq4L28AVx3ah4oy1W1CFc0Im+4Jc/a7OZp2r/6Be+a/2C7L3VtG2Kw1FmBggBqk3lp7PyWOyBlJSRwWFc0bGRnYDcdkmtXKeoeDAUxlKyv5O3cylztJR6JpMhG9fRDiSI1DnKTDgcVI5MvpwBJEKz8+KopCh5N4NP0R693bmt8EzAdOMfpPslganbKFwGRg0Kfwy+0wdCjk/AzPA7ciGnwhElUzBIn4GUrbnKz7uh7q1vI6NPDww01W8A2TYW+NkyOzE7juyCxumurrrOxKIg13hI2JjsO8A90YgXavnjd/WZvI3VtGyNZCbquB4Ya84i8peOeS+Z+jngWVlT668oioKEBIrZwPGM9zLOB2hvEmJfxABELq/o7RWpqI0QlUI9a6HVhrVF76HtHUZyLySway07Q3MA8h52xgVV0t/ZUiW2s+Q3T+ojUwMBW2FUrc/R3AC8jC4j2WYxEn7sykJJ8UCS0h0IIXLHlaraOKTaW1HQ77S0vHR27p5eWqaY1IvbX5ugb3PglBDFeEjYnwwLwT3RTeu1epF1p68p48lqxcxXnzLw2Z3L1j1P+D5EwPJCl4k5Tn7796pQ3wXwQ8ZDfLdguK07iY54hjJMk4ifU7x0FIeOJoRBbZa/w+E5FSHkfSDiwC6pEc770RHf4DPI5c+V0LFNbVoZBFaoBxnjE1cMg/5ZgGRKu/KCmZf1dV+uSC7w8Mi4nhvsoKDgrw1BIs8iWU5Glv19p5bcPt5GS6OhT2NzA1BlspPrp1RZm87kEwIvWEHsbHa8orISdTsbc0eOSMGX/eM2HeyW6Kxt2r9U0UabHmsO6LT7h67EvA2SH14y0jDEBCE0ORFForylHqctEvIpI3M+Dp6pv5V+0IVqPojxCu9zn2AJPj41lmt5OEkLhHEV5LU9y6t4VvQ7T1PJrO3wuoQWLdq/CNwBkNVEfCMWNh+E74aKtiUEQkO70klIUI8Tvr6rAAt2vNUJoWLO/EZoEiX1pKnlbqcnFHjY0lS3UjGbc3WiU5JoJJR2Vz45RCMtOheC9MOqp1ucUTenjvPM2cObC0lcgZM/6856LDxK6UygVeBLIQv9WTWuvFHe33QEfz3asLqavZygsLX+S5+XPZOGcua3Nal2X8ZQSH1hwPHKRUi5JCS7qyf+jfJfHvMoDXGGkc69m5OgBZSE6KiuIZu71ZpMsrwF+AQ/G18AchBOxJbeA5phQh9Vqa56YZAtxkgczp4PoUnl4EwyIjm8Xn+4/hF2TB2uh0dCjyZZfLRVYGHYpW8baefeSWEK1pT+hhTIymd++Wx+Idf56WpvnuO3j4wQIz/ryHIBx3sAG4RWv9g1IqEfheKfWx1vp/Yej7gIX37lWLNYe6GqGlOruvLLPuy49a3cTkLyMArW608V4QchXs0JpZSUkAzQjwBLsdF/AsJ/AONzKbi3DTwG+IJPL/HA764UvE/YEKxKnqyTPTuIAgUswMYCw0Wvlu5APbG9HRvY/ZDtTUw1dfwu9PgGueife59k/q6nih0tZMlvkYWbAq3e5mi0Vb0hPkWq0UltDusL9g1nNbSNYTelhXB0VFLY/Fswjs2KG5+Wbo3Vs2PX20pZw/HZ4R8jlNdE90mNi11gXI9wytdZVS6mfEz2USewfh2b267otPeGHhiwapg3dSsaTU0FL++ssIoZDV+Lh4qtxu5lVW0B9YUFnJTldDMwLsrxSbtGYqvbBzPu8zA808hiK5YG5Dknh5E/E24/hCJDLGO+8MSLz7zUg8rofYMxCna5nR5njjNU95vkVAn0/hpFNh92HVjPvKztyUFMZEx7CtwdGYuMwzhl+RnbIXxsYyw1aOA5F38mh75Eua1cq8uBSmTqn20dhDIWZvCSUmRoj5rjsCyzjeVj3QzEl67Ygs7rpDNPbJkyErA0pLFdcdmeVjrVc7XBQUuXnoId/omxunlDG6b9I+c7qa6ByE9a4ppQYgCfm+CfDeNcA1AOlZfcJ52n2KUIpnhBNJqWkcOfZknps/l2BJxSTlb/tCIVtCqcvF/ZWVfIFHDNLMsdux4EvSO7TmIGA1b/En/sln3MXrvMWF/NQoeSygaaNRPpIrxpPc625Ex/uVppzs2XhF8NAknbyJOF3/Fh/PBXHx/OJ0cputnC+Ndj9+Bzsr4JaT4LavNMfbytGAi+YLiKeP8SXFRCLS0ZnIQuLAV6YKJZ3AubHxfH/IbA5PXtKmsL9iu5P4eNHFe/cWazs+XjeTcbyt+oJiN243JCfRzEm69LRBfLilnDerSnE1KDQ6YB8NLkhP85Vs0tPhtk+2kZNlMXX3/Rhh26CklEpAKqPdqLWu9H9fa/2k1nqk1npkYur+Wcrsq/dXMPXMccyfdCdTzxzHVx+s2Cfn9cgyUdF5xMaPICo6r1lSsc5I+eu9MacEuB9ZsZ9FrNqDEavZiUghBcAsphCBjft4ngasjRuMRgDPINb1SoTcv0Ycq7HA2Ng4piUkMlQphhv9+Ufw9EfSEeQAK+x2zi8p5ienw6fm6hENsPFzqOorNVUzkHj2Q5Enh1+Ap5HskKfFxpPvcuNGFpANxpiqgHkpvRodp55c9aHkfI+NSmRwWmybLN2YCAvllfDgg/Dkk/K7vFJe98BbE3/qeTeLHwFLBNjrxEn67Iuah5ZonlhfSGW9ixWby1jyKCx/VbP4EXhifSG7Kup9+liwEEoM+Qjkd36RZt4CeOp5d2N/Zk3U/Q9hsdiVUpEIqb+stf53OPrcVwjVAg8Wfjhs1JiwWu7BxhNKUrHq8gnItp/wwNuBWo8QtKfc3UnAcYglvBapgJQHJLMXC5P5nv/jFS5mBMvZBPwZcX4OxjfSJQfZbfp6bQ3pSIRMsAieHUjcez6yqFQBzwR4gnj4UTjXAa8abf8IPOzVpgDZUZtrtVLhdjVunvKMKRtIsiijopSDWbZyPie0dASX3zqWgldDS9vrkVWKqh1kZfpaztmZiroGd2PbQDlZevWCqKjmTtLfSmsD5m/xf33AAEhIgBtvlCeF3bshJQVGjPDtz8z7sv+hwxa7UkohxtjPWuvwJ6LuRLTFAm9v8YxwjicpNY1Bh49ocSFZ8+7asFVi8jhQT0CCKzfRlDKgALHiPVb1nxEpxQIoXieOM1nES5yAeNfzkQ1D/gU5yoB1iKVsR6JpRiN52O3G78HGa1GIVHK+cexq43wacbIebBxf7pBUwHOMT/djiBSUZ7TJo0lmGRYZRbHfmEqAPQ0NjCsqZGFZGU5k4YLW0wlkX/eHUKaWNTsrmPzhFpb+vJMl3xeQX+hrOZeW4pMmIFDVo7IyKC6mWXqBQ9JiA1ZI8n7900/hsssgNha0hrw8SEqCiorm/ZmVlfY/hGMZHgNcBvxXKbXeeG2W1nplGPruNLTVAu9I8YzOGE9LuGX4+wjFhQcK0Z3tSKm7/gjJT09M5NGqajagGy3hEuBQpfhYv892IJbeXEYJY3HzF0RDPxYh2M2IrJNh/PRD9PWViOTyDvAPxKLXwBXAH5CUvyU0Wdf9IqNY63RwL+LgGQN8eBI4boD4y2CMXY5XwIUJiVwcn9BobadZrdyXkkqerZy+RmGRWUnJLPBszqJ5Dde2phPw3wTkm+pWCHTaNPlJTobKcl9nJ3jnZDE09iI3bg2JSTB5slj4pYbGnpsc7dPWo5V7Xp82pQCX25Mh0nCa3igEf8MN8ndSkozjr8MyKbY7G8dhbmbaPxCOqJgvkO/MfoVAG4CaIk2aE2k4imeEczytoa2FOoLlL59ts/EZTTLHiQjZ3gwcEx3LXGuEz1b7O4xC1wVAJv0YxnoczGUyD2JFdpKejzhOZyJ5W6ApUqYPQqKecnjf4Os8vQmRhLYDPyGa/R6ngyHAxTTtrh2SDz+kQu/jYcgHktv9KqCXxdJMQvEPBw20OasXsmDsNZKghZrVMVAYY1ZClI8kkpYmssoVV8CzTyqmj+rDkdkJzfryTyWwp9LB+kI7Bx8aQ2pshA/hBks7cHz/ZBKirLy4dY+PVJOUBGecAWefDWPHwuRr4ZisBF7YWER2pqXRWdvHdKruFzhgl932WODhKJ4RzvG0hMryUp6/fxnnTL+mVRIKlms8EMEdhOjgHo16RFRUIynGK0n9OyMpiRMrK4hmJzV8hpu5zOYdstlEHpJC4Hokxt27nF4UTel86/HdhJQNpCMhjb8hunmJ0WaP13EDkAVi2y8Qswe2nAQ7PoBTEUlnXmUFp8fGNZsT/3BQ/81ZZcAjvdIZFhkZMqkHK0JxX96ARklkxw7Jr56cLE5Tl1M3pg4ItN3fk0rgqR8K+Hh7BRkZ8NZmOKFvIqcN6tXYxrutPwamxlCy1zfOvbQUhg2T999/H0or4NfIKpQVJvzVTf/+Ysn/42E3paVmMY3ujgP2rrTXAu9o8YxwjycQvJOH/d1Zx4OxFs6Niw3YtqVc44F2n3piv+d7Wa1pVqvPdvytWuNEJJREJqH5if48y6+cyAbc/BmxthcimSB3Ihkan6cpJDGLJufpz4iF3wt4BJFVyvHdRXocTaGMHq1+8io4fQIsS4ECmywe/Wh901GwpF8nxsQEPSYQghWhqGtwN0oiDW7P1n9DkrlBjm1pu/+uino+3l7hc9z111exub6KvWWqsW2wPDD+sk5RiebU/kncdUcl6b0gv0T79H3zzfDCC5CdDYWFcOihplO1u+OAviudaYF31XgCafU3k8fY6MBk1lJOmBFRUX4Ep7nBT6OGwIvDCYiFnUwh07iRibzIWdzAsSxhIJIU7Ft8JZ5cJCTxCsQCPwshbI1E3njanoBo/vU0ae1ZCKH/gjhUs4AVn8BZl8KqPJj0luxkXWA8aQSDR5IaEx3Dqt5ZHSqF11IRisFpsQElkezeFraW17VYbu630loy/NIX5ObC9OkQGam5aWohNQ0ulm8sCZoHxiPVbC2vg4PEir/o8Ay+y6/mPUuR72LUG777DgoKICvLLKaxP+CAJnboPAvcg7ZuaAp1PMH6DabVv/PAXI4Y+3OzHaqt5RoPJathMMlmMyJhHMFyzuIi4HDcwEXIRiPvEMNcwFuIKkBywmhEd/du29fo+2okymYGEko5FdH/Gy357fDI0/D5j1JoY0Er+ni4y98Fsoy9d6MGkkSKSjQcRIvl5g5Ji6Vkve9xJSVCuikpkJEOz/9YzJKlNMsDA00O0A3F9qangm9lbA3aze4i38Vo1y6Ri9xucdQGcu6a6F4w70wnIlA+9eNOH9+p/bak1VeXj2i2QzWUXOMtZTWEwIvDDuBBxNl5HJDFhRTg4ALjdQe+7TcjUstoZPNQPkLqL6Wlc3npXp+2W/FN5zsaiap5mOaLwNcviyV/SYAnDW90Vvm7lnKnByP+gakxFH0bvNxcbnI0p/ZPZvLkCtLThdQvv1xIfcsW2FOo6Z0u+r13Hpgnvi9gw96axp2r2g03TYeRIzWlpTDthgJcGi66SI5LS4P8fLj0UnGqAkyZFNy5216YqYPDD6W1br1VmDHwsOF63svdOhoyZASznCvLS5l65jiRRAxKioqWxF1tfULwPgfQar9ffbCCJ++Z7aPVey8oizac0Sz9QChb5luCx9rtp2Cb1riAg5Viu9ZcGBfHazU1/AV4mcPJYAjF/BsLQsR7EEdqDTALCac8BpigFCNjY3mppgZltC1AZJgCr3MPRzZS7EEiY/xTAA87Am5ISaTXT7HNrs+zCWlDvYPX7VV8jSwSACOUYm5aRmNxkVDxw4ltI71AxLZmRwVPrA+eUnfNzgqWfV9AcjKUlgEK+uYKyZ93Hvzzn7J5yTsPzOTJsGCBbEBasgRWroR+/SSFwSmnwHvvibVfWQVXXy0Lwp2zYeljXj6AKXDrqL4MTI0JCwmbqYPbhnNf/eV7rfXI1tqZy2MH0JLlHK7wRf9znPu3q1vttzWt/pbh73Pe/DOaWe4dsUxbyyB5dFQ0s2zlOLiPYsbxBT+wm+1MQDTxVMSyfhiRcbYB1VrzW00N/RDHZwySvqCS5vneBxjjSEGcqP2Rp4Yk4MprwWmt4s7rqn0klhU1dmbaysk0+khC4uufpO3l8zqCQNErLVn6uyrqefyHQhY/6kXa18O118LgwWK5v7cCYuKb54EpL4f//Ac+/NDXaetN+h6H6T33gEXBjVMUWZmKPYVuLApe2pZP0beayw7PZGBqTLsrNQWLGjKjbToOc/baidY2FIUjfDHQOd56Jg+02+g3G/iYBuf2Zv22ptWHexMTtJxB0kP8j1fN4PGarxnHU0RwKlbgK6Twxu+BfyMSy1sEtr77AcfGxpFXW0OukVXybsTK/gkp0OHZ4GQHzgDWfApXT4Yv+2o274I8WzkKxR22ctZ49T8OKah9ljGe+W2IV+8MBCL8NTsreOy7Anr5OU/T0kU2SUyE7duhrh7q6xVbtjRtgtq7V8g7Pl7I35/0PUE/gwZBUiLccTtMPjq70cn6QPEeHn5EM2iQ21gMikhOgIrqpiRkHrIPheSDRQ2Z0TYdR9iSgB1oaC3FgHfirpi4YUREjuWyW2aQlJpGZXkpW35aT2V5aWN/gV4LdI6IiH6cd9W1WK1jEDt1DlprNn7zZZuvwTv9QKnLxXqHg1K/rfLBXm8P0qxW7kipYnbiXKo5hQvibuIg4F1Eh++D7Cp9DXGK+udwyUEs9ysTEngjI5OJSSlMT0hkAYphSLqBBOP35chGqEuA31YDbige17TZaIGtjDS//j1JxgYAS3ulNXOcdnQuKuoaWFdQzbqC6hYTawVr57Fwp94kJP3FF/K6Jw592TKYNw9mzIDjcpLI65fE5MmikU+eDGedBY89Bk6nHO+dOmDvXqira/rfVqZYePJBjTnhE6KsZGUq33w22ZID3zsJ2TMbilj6v51M/nALa3ZUtDgfgdIkmCkMwgNzWWwnMnJyaXBsQ+oAnQoUNLPIjzt9PDXV1Sx/YD4RUQNZvuh+dm3+jdVvv+kj36AJKOkEs/oPGzmaN596AlySrLbB2bH0A2/VjOBWWy2RKgenzueBlFjOjYsNe5SIB9ckvMqq+vG8XHM38Dpz2cXTjbMolvMViAPVW3LJRz6w55QUoxCiLwKmJiTycHUVKxFrfzVwOkLQrwN6L0RsgKKToeJFidSZbfwESzI2LNJXVw91LkpdroDFrNfsrGDZDwWk9ILSvbJVe/LR2c305JbaFdudKItm0SJITRWpJDpaiDoyEhYvFsJdvx5mzqjEahELPSZGSPvOO2H8eIme2bFD0gfk5orGftZZMHOmkHV+PvxteCa5ydGN44qJsJBf6Gb9+ia5pqRE2nuTfd++MH26JjJSZJUBKTHNZBpvn0JLUUMm2g9zBtuJjV9/iTie5wBXY7UqrpmzsJkD9aVFC3A6PsfpEPr46F+jgZVQnwds4Il78kC7cTo+Dyjp+G9ayjv3fOZdO5EGZzaBnhba45i9pdaNg7XUaTn/dNuxHBZp7ZQoEQClYFbSzVy491yuoJgXkB2lU5CEXWnAowTWy+MRPTwasc5LgEXVVQygKWtkHjBEKSYmpXByjNQyffTTci79G0xKg/tL4Xaa52dPQGSYGxISW43TDzQXHvLvu0qx0625elTTRqHHfyhk8SO+uVmWrfMtRddau+/zq6lzSPoBmw369JHYcleDEPSgQZLc6+GHIS1DrPCyMjjpJBlfSgpMmiR/n3cevPWWRMCMHCkW/0cfyfvLliifwtmNDs5Mxe23a1ISwVYlx779dvCwy/h4ze2rtpOV2UTaKJo5S5eeNiigL8FE+3HAzmJHCmZ4tO8GZ5NCa4kQMvZGIAeq0Eg8Qkn1KJWFsrgIRtLejtCYuHjuuPhCGpwrENGi4+kHAo0xUuWwzlHaYjHr9sITfVPh3soAZvMqorEfQVOyrXrEUVoFvEeTXn4usArJ2bKaJkv7WCRc0tv63qXh5Bgh3vFx8Ry3LpqfrnZQVVpGPM03Q00ExiMLy8XxvlEtgeL0c9B8UlfXeA4f8ndKpaYTvilscoD6aeLZ2VBb5asnt9Rua3kdb28u5f778SpU3eQ43bFDpJlFiyTixXthOOooIe7KSpg/H26/HVa+C3n9Enn4wWqSUzWVlXDTTbJolJQ25YL3LDairXuqLCkuHprG62+UNlZq6p0BRSUwcaKQ+vr1klN+6dImx+iNUwrRaGPhanKWLj1tEIPTAu+MNtE+HJDE3pH48sryUtZ98QmWiD4+ZBgRwGLOyMnFWb8VX8rZjeQtXArk4qjbjsWqaImkPY7QLT+tN0g4D6GgcUAakVHFXDNnfsAFqrUFLJDc49T5HBmVwNwWNi61B95yxiataQAyOYbLeZx3OZvh5NMLKZf3OZJK4AJEEy9AMkFWIxKLf/70PyM7UhOQqJmJ8XFsdDoYRhRpVivp7ghOjIxgfoqb6202nF5XXIA8ESwG7klKbrZw+cfpL0Ri6V+stDG3QmSZfhGRzcg/16IaJYdiv3qoBQWgXbpZat5g7QCyMgMXqu7TF/bsFmkmK8v3vaQkuOoqkWumTRMZJSdTMXGQxKJfVtfAh5vLeau8lOXPKwqKNMmJmpmrt3PtiCwKqh0k99I+fWamQ/+UGJaeNoiPjEpN7gaFFc3yF+DTD0W2ycn0dYxmpoPDaTpL9wUOuNnsSHpcz4JgiehHnX0L8hW/DX8y9pBpTFw82u1C7NABiG3oBh6gKd5jNYqziYgcS0RkPxqcO7nsljtCIOE/A72JiBzP/Fffps9Bg4OOt6UFLJDc80BsLIMj/dMJNN+41BaUulzMspXzGHCkFqv7XeAc9lLCIVzLE8zjHPKhsSLScCRV7lgkp/tQJNvjL/guOMXG7FqN2XUAz9rtfGC3Uwzcl5LK+Lh46vs7GH5jFZ88msa/1jk4vrqKDITYXcBV8fGcFhvXbOzem7hy0EhZcRhu1FDNs9l4IyOj2SatXW7dqC1fd2QW024oILkXlJU2aef+G5aCtSuucbCnKHCh6j17ICbWyA75bPPkXm43TJggkozHQTlwZJPUcmR2Am4Nr/9aSp8+It9MuFTz+PJC3FpjifA7X7FmYfFuzhyUygfbbEbYpW605i89KIf0wyOZuXq7z3HFe0ETfOOVifDhgCP29saXB1oQYDQxcS/iduU3JuzyJtMGxzYsERm4XN8ipD6A6JgxaGJw1A1H4j+ux+Xqg9J70HonkdHiZI1NSAyJhK+ZsyAgqTcf72oenzOe/kOGNmsfKO79vA1n8NYsWk0nEOrGplfs1TgRLX0rErd+OABbUcziPRazisvQLG+souSd492KEHyg2qUgy+ubSCRMHL5STZ6tnDHRMaQWReBKcWEZU8eULalcHJ/ARqeDr+vreNlu58uaGl6x1wR0jHrCNT+pq+PFShvDjY19HonKbix8eTYbA+Ij2Vrn5OpRTY5An9wsEHSDT6B2AJM/3MLEiSLDREfD9deLTFNeLvLHC8+LNT5tmkgqiYkivdx2G/TvL1Exa9aIBu42CjM1bQ6CXYWaK66QBcATx56WqnG5FVdcrRtzxXsWCmWFN38tb/aEkJWpSIiykhRt5Yj0OCZPtpORDiV74dT+SRyaHmc6S/cBDrgZbW98eaAFISZuMBNnTOTIsSc3hjEGIn+JsM4DNuB2F4OyINRzPaIaZ6PdQ3C5V+NqaPkpItREYb7jlQWkwZnNrAnnc+3d8wMuGv41VOHYFjcutSVS5KnqKp9EXqORWooHAQt5hOn8iW0sRvExKRQymqZdqW7gwZRUki0W7isr9dHGr0QyPYJo8b2N375eDSW+gboo4tbFUj26lvSXUmSVAF6w23kcOFVrCpCFINlibZaiN81q5eSYGOZWBJaoPCmM6+4+gd8++r4ZYSXHRIS0Fd+/3SajpN2ECZrjjhMH6cqVopV7HJXvvgubNskO0qoqePllWL5c3gNxrl54IYweDbfe6J9orInMz/6+kK8AACAASURBVDhDCDojA/J3g8Wi6SXZgLniiiZH6403CsHbbM1z3WztXcucNTtwuX2jcu66o5KLDs8wnaX7AAfcrLY3PW6gBcHt2tVI6uBNptlIyYcBREUPxO0eT2TUQONc8wF4fM54r8gWT3kILzpSfdj+y0YGHDqsGYmHkiisabyraVpAhuN0yKLRf8hQ6mrsLS4OLRXr2OR0cLutnBVAXitRM+J8VD5Wbg5wI7KR4nY0O7mSGn7kGibxBHNYjThLX0FIfEy0WK578LXm9yDJwqyIg7UIkS98vRq60TeQ+FUc9lG1fDqogps+s5ONaP2zaYrK6QXcW7aXEhS3JyVxWFR04xNJa7l10qxWcg7Noujz8H21PPHer74qqQLS08UaX7euycKuKIOHF4nlXm4T0i0tbcofU1gopF5aGjzRWEaGtCsthd274OLDMkiLi+CO2wvolS6LBhiJxjJEsjnlFLhhsuj2JcYGpeUbi7nxZvjXv5rqp0KTnt7WYt8m2o4Dcnbbkx43lAUhIyeX+tpNSEmHgcB2XA0OFvzrnWYk2n/IUGZNOB+nYzWiCvs6WR11W7l/yrVYFETFDm6Tk9ej8V92ywxe+Mf4ZqGRkMPMv5xLRFR/Ghw7mHjrHZz8x0sC9lG5/F3Ouuxsn/dW1NiZZSsnG4nNeQxR/INFzQRKElaKRL58brz2CpuYwbEsM6qP5gGDEKu9D9LvzgYnTiQKJpsmbRxEg78ACZHMN9pkIvr7XV4O0bgfY6BGsXlUNas/8911+obRhxuReArQjK6sYBCwx8gMOT4uvsWMl6UuF3t+KaSiriFs5JUcE8Flh2fwzAvFzdIAfLxSsbcMJh2VxYCUGG77ZBszZ8tGpWnTmuLSnU6YPk1RvJfGRGOF3/jq3bt3w913ixXu1vDPn0uYfHQ2C08+iBmrtjfuYn31VekzPR0++ADcLrgwN5vfjYxr3E06cqTmkUeaW/Omnr5vcEASO7QvXW9rC8J/PvkAt8tNE11tQFmOJzGlVzNdu89Bg8k7/0I+fu1MJPiuBhEocpAtNM+i3UNxcSK11fcDUTx5zwWtWtr+DtOLJt/I/z22BKfDa9Go3wpMp8G5FBjIM/PvQSvFKRdeHLCPjXPmMuPR+4CmmO6mKxRS7E3wqJlAVu41CQmsrK5qXG5OBa7mRzYC6WTzKw3soAQ7suQ5tZvZNptP+oFFyMJSgBD5l0jUTIIxpiIk98v9lZUkWiyMj4vH4lTUvRzP5s3VAXed9kLkHU8d1sHA00A02ueJJJBE9XatnTtqbOQ8+Ca79zjDmtBqYGosuVm+Fnbf3oqzsnsz8vci2xTbnVw+PJO59xaDxZBT8uG66+DNfxltj04gOSaCD7eU42iQUMW0NLHSTzkFvv8e/v53CXucNg0e+76A247ty8RhmUy7oYiEZNH1H3vMd4F5bF0+k46U9ANFJUa2yGm+9VPNVL/7DuYstxHBFoTK8lJe+Mc84BB8UgBEDgjomK0sL+Wzt97ENxvKKERY+JWmHINpSKbxEpwOK7MmnE9E1EGNFrz3QgM00/hfX5bHX6fPZPkiedJocG5Hk06DYykeeQY2sPwfJ3DMSacF7OPJe/IYtnIVZ112dsCY7jQkBnxBC1Ez/lZumdvFkuoqXkEKUK9DEnyNJYYavkfzFbn8kQsRy3tbQ9N5/wMMAa4z+s5ALPh1SH6Z1UjIY9PM+pJy9ieJfFhUHXTX6XFGv57g1AHGOVqK4y91ubijxsaipZpBgxxhT2glcgzNokxGHp3gk1e9sFhujLdlP3Uq4Nb0OljG8eGWMp75sZjHlgmpf/edbGpavVos+8xMcbimpkoEziPrd+NwKCb+LhOnCz6JLvFZYHJz4c9/hiUPSUy6925S7XIzLi2N00almqS+D2HOdAfgHSNekr9LpA3nLrxFhwbnDmLi4tny03ofKzvw5qVDkdpCBQiVbEBiQuYCSWg9CadjJU6HbNl5fM65KKUaiT5Q5keLNZcBQw9nycpVjSGYM/9yLiIVeUcG9W/McxMsamjNu2s57IxjmskqxcDbGZkM9tuG7w9vK/cVezUWZN/uHiAZscQvirOyvGYxDhZwCf+fvfMOj6rO3vjnTkvvjYTelLYsukpTJIguWAHZdUUXe0MUERAQC+AKIkVXXUTFgoLYFcsPu6Asgp1V7FIDpJHept77++PMnT7JpIAE8j6PD2bm9sD5nvue97zn73TkZWYDJ1jMHl19F7xj8/RrKASuAu5Diqr+d+cflN+tqyWtA9zaHXZ8IsE8E7gAhQkxMVxQV0dHt9Z+ns9voj4df57LRbuA5qKW0Gg31H4PBDkk6ll4ebnXbsBug2d37qeoGBxOjZwO3ms94wzhw8vKRHHz00/y/+XlYjvw+ONw0xSNB5YVMenEdhQUan7WAnl5QuPExGh8X1hTrzNlGw4P2p54ExFIV/xzxmxU536kWd0rxnM6VW67aCzmqG44HXsYe9U1jBx/cchirEz/XIYQC52Q8GVAGuz3IETBeHRNvNMRA9yPw34xwc6Pckxr7W/s/ukHuveVKlbxgTwuvOFm1j64zG871eXN+utTDf34zhfcc3p/j6Z7L3B7YlKDQd0XoVQyI5Au0wtqa5ibsJI7q8azkOV0ZQMaB/nJ4fCjc+yaxjCExNqJUEGFyKDr9gRWLLxBeW11FfMrK7jtSjh5FFz/OahWOC8ujqvjE0kzGpmSKBLOH+w2FlVWsjYCHX9Ho5GC4sg55UiGS4TyKg9UlPxWUkd6qgTw8nK302OazCj9+GOhVOrqdOrEG/iLikI0Qmlgt8PTT0tgN5lEbWOzyaDtjEx45NsCEhPEaCwlRY7ds6fw7pmZ8NDX+fx0sJYL+2aEvKf60DZwo+XQ9vSagFCyxjVLc5k4fRbPLluEw5aEBOV7QLsHp2MjTods9/IjQ1j3xGNcN28h1869h8fm5+KwpSK8+gqkDUdDyncWvIRCOCPbE9xXJd2vZ1w4jLeeHoyww/uAeaxetggNhTXLFnkWouFjx/HZ+tMwmjqjuvL8CsENFYlTPv6O2bn9WFhZQTdF8eOwI9G1h1LJ6Bx3J0Whs9lAPFdQyzcM5GHmMIHc8nI2ZLXzm0NaqroYU1zEeiSoT0JooWJgXHQMuVarn3IFYGFlBVuBTh/DtjHw56Gw6mMYW1PD1fGJgPfNYoDFwuiY2Ih0+mlGIwtik5k+uZzsTmb2uzn2UAEqkuES4bzKfdvvK6xOtu6r5ECxxtKlolG/6CIxD1u/XoJ5aam4PvpZ/KbBwIEEadM1Tb6rqZEs/6GHhHN/8kl/Tn3qVDEUu+8+MQ67++5Azr2Cj/dWkJNliHh4hq+mvqAILu2XyageKfXu04bwaAvsTUC4Jqcuvfsy/f6HeWDG3djqdiCkQICMkeNx2Gfw+PwbeWj9Bh5ev4GPXl3Luicew2S+F6djD4NHncvm9W+hujr47KvrQ/zVLcIs90bPrPueNJgPXtqItWaJe7sTMBifZfXShX5GY1veyWXh86+HLMQ2VCSuLCthoc0mBVSf7ssqVeW+ysoGde3hRunVIEEYNLopP/I3bT4/0ZvemOikuDwDtvUAm+dy0V1R6KtpjCegKclq5dWMDGrcmXqa0cg2u50u7gVF+x4sxXDm6RD3MXRWlJD8eWMGkIyJieNUSzTWaaF17BD5cImGvMp1F0iXGjww47jkaEpMVvbskVmlTqd/dn7woExLap8J+UXgcgEGWLJE6JUPP4RVqyTIr1rlNRjTryM5WfTp8fHwyy8EDdZOT4e//hUuvVSNqNbg/0z0+ygENEb1SI3o2bfBH21+7E2AP40CvnRFl1790NRihCfvgpcNBm8IO9Ov23Xc1Tfx8DufcO6lowCNrzb8hqYqSMat71uDV8WtH6sYmIxYaA2me78+dOnVD4d1NzIyegrQE7t1B0ZzFwKNxqy1NXTvOyBkMTgxJS3sd8UH8uhkNvstMR0VWFBZwUY0vtU0NqJxR3l5SO9yXSUzDFGtDHHf3bnIYtDPbGGXptGFhTzARH7CGZLf1heIDwj2j9G7QX0Xgo5GI3s1WQC+0sC+AY4fCDUJYhrWFB+cQI/2NKORk3uFV394A7b87BuwfVGfV7keCKdOg46dgoPqb+VWDh6UoP7vf8Ott0qWfckl0pV6+eXisHlmViYrz+3BHad1IKedV3OuNyF99ZWMxysu9vduLy+X5qiyMnjrLS+to39/sBiGD6///oKfSbD976rviur1rW9DeLQF9ibAd4hGTNwALFG5HrrC/7szMRrtGE16CMtFVN/B3u0Abzy1Eod9HXXVj6Np60FREbrlOGR8hB0Jg3o4fBxhlZ8AuvLT11+Rv2cnqqYiv9o4wICmgcu5l1ALUVOQkdORvQ6H/3KlafiPBPEWLEOht9mMC7gbea/5Amky6m02s7amGg2xDugCDKYvp0TfEzKbnpWYyLV4/WP06wm1EKQZjYyLieFsZADHzR8BGsw/vmk+OM9VVzGsMJ/bDhYxorCAN2trGtwn0uES3kHXCtdcbuCWKYqH2vFqxb2+MfqxDh6Ev/9DsvD4eOHeTzxRulANBqFQJkwQflxHeqxXcQMS1B0OycoPHBB6Z+pU78COhATJ7uPipFHKZBKLA/17VZUuWL0rtaHhGZlxZgoCFofi4oYXhDaER4tQMYqijEbM8YzAE5qmLWqJ4x7JqI+uCPwO8KNbQvHWxQfy0EjCtzhqMmVxwXUXoQCvPrYCp2M9okG5EtGQ9AaPjdU+IIdV994l9VMfYkLThnDWxZfw7tpcDMaOuJx7+OeMOQBBap1IMeqqGxn25MN0MlnIczqYExXFospKvkNr0A1yXW0d08qr6YRUDcCrGz+vuAgN/AqrgxjP29Y5XGD9jTOjP/Qc583aGu6rrKSHe0TeMKCrooQtdJa4XLxeV+epUvzvVzjrAnguNpOesY0bWK0XYY9Dpj3Ndr+hnBIVTU49+3kDdsN+KeHUJfriUFIiQ6cnT5YMt9htm/vCC5AYL/y6L/deXCydpc8/L0H3Q3MRz/1QxNndU0hJFEuBzEwxFTOZhIo5eFCKqRkZsojodM2OHRLMr7pKbAi2b4d77oYLjk/jzd9LWLVKtlVdcHrneHaWWcP64yRFm7i0XyaTJxd67uOii+D5NbRNU2oiFM1dwGryARTFiKSNZyLR5UtggqZpP4bbp1uf/tqC59Y367ytEb6uj9baGs+fGTkdqSov5dbx5xBYHI2K7YzLsR+DoTN22/fI470OmIVYBXRGdO+a+z87wuv/7nPmHky5bzo1FZU8s2QBJktnHNbdKAYD5qhujepqDTQ5G3v1dYwcfzGJKWmUnd6fOwJa7UONlxtcWIGVZcQyKcg/5n5gJfC1zz79sVBl/IZaLZ2PMkeSbKigxOViRGGB+J+79z8NGWnXz2wJGdR1A69tPn/nBygK96Rl8GeLGQWlwfvXjzW8MD+oSSsbWJSeyQCLhW+G1+8J01QFiL7fzjIrq38oIikRnGjMnev1jbniCsg/AMsDmojGjJHhGoriXQAyMkSqiAqLFkumfvfdQuHo+958s3yeni4eNDoucTcrV1fLNs8+CSVlCv9+WPPw+4mJsjhYLKA54bI/ZdItJSbkfb/3eymrvisiK0O6aVuywetowZjnf/5a07STGtquJTL2gcDvmqbtBFAU5QXE5iNsYD9WkZiSxvatm3n87jvQSMJhK8QSJQ3rY666BktUd+x+uvau2GpXIQz02XhV3DuRbP1nhGGejDTTVyKSyMChcvmgwepl9+F0/NdtMXA8uLxqnUisi0Opgd54MpeR7o7VlI+/Y8NZA+tVkeS5XJiVHKzaeBxMIReH547095XbA65+Hw4eSZrGP0v/j7sr7uL+lOkhG6W6KApJhuDz6mZl7dHYEXDsomiNpIVlVHwWR/L7DRt06ffQJUDV0wGppuhvKO/tm8aoDveH3L+pQT1QTTOxbwaZcRaWfr4fs1nz+MLs3w/tA7pU09OFD4+JgqQECer33+9tUFq8GG6bBempCklJXv/1tDRZLIYPh1df9S/ClpbKIpCaKlSN0w4dsmWfadP8F4fJk2HUKFj5ThEdsuBgqRIUuEf1SGVwh8Q2yWMLoCU49vbI26iOfe7PjnkEDqiuLCvhsflzsNsW4rCVA1ux277HbtvI6ytX4FJ10y6QsLML2ATEYTKnYbacRkzcmRiMDiS/PQOxrroN8Th0AdsQdnoQwsWfimKQf+Dewdi7CVTr+A7iDoeGBniD6Nx9C5aB6Gg04tAOAPk4eJhqzBQg/iy1CKn0CFKN0KsS9yQnc2r0j1wR9x9erruQ9bVD/JQ1+tPSqR/fgqbvZKPv3U9mMPBnRSEXhTuiUjBaoHpIbb33HngPewPO/Rui52+Ip9+0t4LJ7+3g0V/yIhr4rMNXObJylcoDD2ms/qGYbinRXH+CcPFXX6aIH3rfDEpK/DnrqiqZnlRng30Fkqnv2SOZ+0svSRbvcMGYjhmUlyrs2CE6+IkTRQb56quirpk6Fa69Vv5UFKFuHA7h28/pnkJhMXz6abBSJi0N3nkHOnWCkkrxe39sW0FQcTQp2tRmEtYCaImnF+r9NYjfURTlWuBagPR2R3/cDzXkonDfHhx2B/AoQpm8jbzA/4TT4cJg7Ihk5hmI68k4xHewK05HMRdcO5kTho0gI6cjX370Lk8tmo+mZgHzERus6937dkbWbAVwYlDSWTH3dlSnHQlD8Ugo2ohuJ9xQMbWyrISaygr3AO/6LY/rc4VMMxpZmhzDtPKTMOIkB40i4I7EJOINBk8DkqppjI9PYHRMDDWaFCpfqZlNDvuYVf4WC5JjQrosbrZZ/ayEr4mPp5NPZj8TeBY881DTjEbKtrgouagSR7oT88GG/0n4et90VKRwPC8xiYvjE+rdL1KpYyjUJ38c1jmJtBgz2wpqGNAzjj6ZsaTFmphyYz4paRLU9elJHTsK9bJ3r1c140ubrPq+iKHtE7nhhkoMBvjPf3ysCW4El7sRym6HYcPEriA9HcrLIDHbxPAOiSxfXoGiBEssFy/28vPTpkF6Kk3uzG1rZqofLfFE9iENgDo6IFyAHzRNexyRcdCtT/+gwH+0oLKshN0/b+exu+/A4UNZPDbvNCTQ+rLKQ5AmeIAtqC798+FI0D8fyTHvA3rx2uMriHZz1r3+MhCTyYLDvgApb+QjQfp6pFXHex6XawQu12uYzGMwMBTVpSELytmYLZkoSmW91sW+i5SmaRiNQ7FE96jX8ri+4H5qlIU4HP6688rKoAakzTYr44uL6aTAr+72/pkskydUrrIxK81ve8DLu7sz6mHVVejLmX6uAyieoA4QvzWWkosqKRpUQ/HrMQ02I0Gw900kipqGtOn1wVdN49vZGt3XwNLNeXxRWENGBqz7vYQzOyd5Oj9LSuDee70BtbgYcnKkEJqYGJo2mXpTFYPaxbHTWeM/Ei9DoaDQ+0/3v/8N1NAXgwqPrJDFwmMAVikKHV1O2b27qHLyCzQKq+1EmwxYnWrEQTqSBq9jHS0R2L8EeiqK0hURWl+EV+zQKtHUQdd6AFQMGThsafhSFgZDJigx+AsCj0ey8mcCPu+EFD+zkaDuNeta++/BWGI64bLnYTB1xV9XkorJfAZOR1rA8aSv02TuiNORh+p6A31EtKqO4Y7HV3H8gJPDPotAXt0clcvNi2+lS69+9T6fcME9VOepLo3UaRy/4dCat0B5BWDheGp5hzfrZnJF/FZPUN1mtwfx7hnAWfhPXJqXmOgXiM3FJmp/MbJrYBUPPVHd4NAQ32DeGIlkuOAciZVtKDXN8A6JzPx4lzQpuQul27bBzJkVdE6KIifLwJi/qcyejZ/aZO1aoU8OHvRq1bt393rLxCVq/G6tobQiwHagSGPRfd4mpqefDtae790ri0X37iKznDIFxo2DF18MtjBwuWDt7nwOlkBKItTUBPPugWjOW8+xhGY/CU3TnIqi3Ai8h8gdn9I07YdmX9kfhKYOuvYLgLiLk75eLJ7JSYH9lscj2bbv578BC93f98I/SHfFXrcP6IrLFeiIko+mKRhN1bicgefZj63udzTN32/G5YxjwXWXcf38RSHvM1SXrcnUibjEpIgWvVDBPVTnaaA0crvDTseAO++AVAdgN05srKh+gL/HnkG8oSbscfOBu9z/7UYWhj6WKL/rKXG5eHiNi/kp8I2biw81NCTSiVHh0BipYyiqwVf+GN3XwG0bd/OPCfDBBxIw334bHnsMsjLh6e+L0DTo3VsKl8uXSxH0mWeEM7/pJlGzLFkiXLk+xCMjw2v+VVXlllJmKRQWQ0qi5tfEtHSpf7AuLpZC6ldfibFYSYk0L730knDw06bJIlJYKD9ffjmcf76Xmrl7gcZdt9cfpJvz1nMsoUWehKZp64FWr19szqDr4AC4AhhCVEx3NHWfZ3KS1xumGCkZLkT48WHo2gqjOQ3I5/gBJ/Hjl9/gH6p2IY86FxmmPRixwCoB/o3LOQijcSjmqFwgG4dtF4ohFk29GE3Lcp/XX1LpdKzl8flXhrzPpo4S9EVgcG9oCpE+yMNB8HJ3BXAAO7fET+X+6vUsqLyde5PnhDzubk1DxTuYMB+hYeIUye71rDvP5aJgs8LAEG8Q+jWFeoMINzGqPkTifFifb0pStMlj/pWVoTB8uMbatTLE+qWX/KmRm2+Em2+C7EwDJoNKuhpFmWajUyd44gm4+moJ9mVlEvB9973lFnj2WRnkcU52Fsf1i3EPpxbFTEmJFFNvuEF4e/1t4Jln4MEH5VoKCoSCGT0aXn5ZFonsbPGhmT1b/h/cwTlLRug1FKSb89ZzLKFtifNBUwddQ6gA2BuzxcwtS2f5URb9Bp3C+tUreXPVk8DneMPWMGAuUTF3cerZA9mw7jV+/PJbIAEJ3p2RzDsTCVMAMzEY70d1FSGZ/2zgESzRPTjzwmGsX/MMUTFdsdXtwjsC+gqC/Wa+RFHS2f3zdvoPGR50b2OuuoZ1T+ZiasQowUD4BvcSl4tOJnOQl4v+nT7I4yf3neoWafMSk3zG1P1AhfYkT9Rcw7kxb3NK1GeAl/teW1PNyuoqeiDl6EygEoVxMTGMLy72y7pPiYpmjwbbEqHdYCh8P/gNwldeWQzYgBy0sP7s9UEPzqEQqW+KHuCcTsmOn39ePNQDB0tP7NaeeIuR6L4GZm/Y7THrev55CeRpadKRmpLiv29GBrz5JhSVaJx0crx7ipM0EbVvL5LKq66SwL1ihXDpa9fKsf71L++c09tvh1dekbeCF1/0Go6pqgR48I7us1obDtKNees5ltH2NHzQnOw09Oi8hUGBMjEljZNHjub9l/+LtcY3wGYBV+Owu/jkrQJUlwVv9+hGYDRwHmJu+53nc9XlP1ICcnHYnbyzdq9bs+7bQnMewRr3UuB+bNZslk27ievc1FNlWYl0yz65EpO5M2gq5142ytOM1BRsenuLp4nJN7AOsHi7Pn0DaH/gdOAU4OHUdIZHR/sdb2bCYj60nsErtX/zBHYdK6ur/YqzpwFPp6VxVUlJUNa9Iasd9yQns3BoGTfcCrfuhnuK/DtXdZpnMVL10O2Cf7Tb/K6/uajPN2Vwh0RPAPMNcEmJkJameTxdvJksdPuLdHt+m19NcpLXp/2FF4LNw3w91vftE3kiGnzn9ljvlhJNTgb8/e+SkU+YIMdq1w7uvUcakOLjxNI3PV04fFWVIO9XnJ0q2f6dd0rWvncvxMfAXbcrEQXpNr/3htH2RHzQ1EHXOnQrgd0/bwegS69+IQuxsoDsRkY164qWYiRszMBgSEPadfTAn4tk5O8jipfBmC1dUNW9KEq2u+EI9/apnJTbl22f7cFh6+8+boH7eGsAK6LGOR55A1gBLACexGGL4vH5udRVV/Hs0nvd0swt7uNs5PWV5zNw5OgmB/bKshLm1NXxaT10RiBPng8cRKGfOTiLizFYeTn972Qaivw+D9e85DuFSf9cp1zOj41jyM8Wyp2FPHReHB2f9+fOdV+aeW7bX181z6iY2EZn7eHg65viy12Hoij0APd9YQ0PfZ3PZZcJV52RIcMvLumT7nGCfPSbApJSNSZOlGlHoXTms2ZCeobY/l5+uXdQ9i1TCuiSHM2WfZXsL5JAXlLiz8vX2uCCnmm8/lsJ06bBww8LTfPSSzK8w/dc2dlQWysSzIoKGcJ904AOYS0HQqG+t542tAX2IDRl0LUv9M5So7kz9rrfQ7btb9+6GbFymAtcg8j+LcBKVJeK3ZWHOIz7919CGkbTY1x44wycdhvrnngch92ABGndyz2frR/sRX61i5HpSy6koPsAMAN42P2nvqj8jjQ2XYPB2JFnlizA6XgUGfrRH3gRuAGnI5s5E8Zx3byFERWUA+FxhbRZgdBcdkP8eyDaGQsByHe1o1RNpa/5x7DFWd8pTKGKthlWM47/RWMfYkV7QUPR/Fs0+lqiOC6MmqelAntjfVOSok1kxVtISZQgm5YmtEZyAvTNjPVQO/9+2Evt3HADQTrz0hK4+eRsyq0uPjQUMWGCHF8P+tM/2EVKmnjI3HabZOGrVvn7sN98Ywlx8VJAzckBo1Gy9sBz5eeLDn7FQ95B3CdkR9b124bI0BbYQ6Apg64hsPgaum2/8/G9efzuO3A6NuGlWc4GD6usj4vYj4xs7oUE9VmYzAu494W3SEhOZcrZI3DYP8FfE68A/0KC+Y3IwhED/NdnuxFIwL8JyeKL3eecAWTgcu5xj/g7073NRsSTRiSXDrv3Pny93CORiPq6QtZnFNZYjbimwVWlT1KpJvJC2kgOqtXMTkwkt7LSb3HoabYwLiaGwXW1dHA/1QkxMX7HT9gaS+FfSrEeZyfmF3/1jG/HaUNGZ82BFEo1j2/K82uol6LIjDNTU6Nw9wLNw23fdbtCZpw5pIpEp0mmTpXsWZce1jhcXzvMyAAAIABJREFUmE1wIIDSOVCokdVOLATGj/dm4bGx/pl4UqoE7Pnz5Xfy2GMyjGP7dq+mvaREWueu/nMW3VKiPaqfCquTnWWy4Dcmc29DaLQ9vQA0VcMOgcXXLwls21cMHdj++aaAAq0dcWDIRoLuRvxtsX5Fmuvn43Jp7PnlJ7I6dgoxLzUbb2BPQfj0F5EuU9/tMt3bXQA8h0wHXYF4zVzM0LPHseWdd/A2958PtAs4Rg63XTRGFgD7Hk45+1y2vPsuBlMnXI7dTLx1DmeMD25lSExJ49K5Szlt/gw6mszkOR0sDAisOtICCqr1BXlFgTsT/8WFJS+TW3QjvZXp7NFgVmIifT3FVqPH3XE9uoofLqirY0qiN+OO+zoaxapg7WkLCuyNfZtoDhrjm6Lz7XfdHrqgGKgiKS2RYumjj0p2364dzJgBT/6vCJNRCaJ0Bg8W/r1dOymAxsbCddeJ14zvcUtKhKvv00e+T0yEuXNF8QIin3TY4aGzutIxyftsN+2tYPlX+WhAWjqUl8CkE7MbbDpq6z4Nj7an4YOmath1+BdfuyCDqb08uq1uB889sBQJrN8hGfp1gIPQ4yJ6IurrycBtaOrrPHLnufx90mSc9t34544lSCCvRXrEfkS4dSVgu71INm/Av+g6AljPlncuYOL0WaxeJnUGhx00rcBPF2+37QRm4HQsB7ryyRvrgHlgmwl8x1MLBqNoGiP/dknQMxoyegx9B53qv3iG6VCFyLXjx5k2E8UK7NzMcu1l4tni6Wb1nbjUWYFcn77nQCrFYDPQ5eZ2GKtDB+umdJw2FY3hkcMVFEOpSK7sn8mq7wspKYFevbyqFFWFlEyNCRPEiregQALzN9/4Ww/ExkpQHz7cX+542WUio3zmGQnmJSXBBVqjCfaUWz2BvcLqZMU3+RjNgd2v9evZ27pP60dbYHejORp2Hb7FV01LwmG34+XRFeApnI7eGI1DMVlOw+kuTvoH+GBeXSx6lwIPorpUXvzP60AtimEomtoOUboYETrld0QgeB0SvBORzD8HUcA8hXDudxGqO1Uf8ffQ+g2e4Lv9882egrLTsRuNdJz25fh2xPpLKXvyzJIFnBym0BpIdX27eQonnPJQ0HaN0Y7nuVwcxywqOYsreJptDKCTYvML2pE0RgGeoK6hhbTybWzH6aFCYMYabiHQg/7OMit0FaoD8PD4Re7xeIuXSCDfts0rVywthfbtQ1sP6DNTZ8zwWgZ/8IE0KBUXi0GYL1WTkyNZe36V3XNtRTUOUpIUYhI0v20z08P7yLR1nzaMtglKbkTiXBgJho4+nwVrX0XcFrcibTVbgChEvNcfS3QPLpk6jaiYHu7z/cO9XRJu70EkUM5Csu6rgalIc+9WhJ75Ek11ubfXgM1IqNoK1CHc+lb3/uuRRWKz+1x60dRvBhJQ45F3+o7GGzr6fB5av4E5j97DwudfB60cwvaFyoJkMkf+7KrLJrDp7S1Bn3vULT5nCTeVqaPRyD6qmcPVDOQLvsESFLQ9VAoKA9zujuGolMLrSim+sjyi6w+F23bc3eR9I0FjXSK/K6ph2Rf7WbPrAJPf20Gs2cBV/TPJ3ydSw7Q0kToOGyZyxQULpIloyBDh4H2tB8DNqSdJ4Lda8VgGHzggvPo558h3gVORKiogO8FChdXJbyV1RJsMlFVo5Of7b1t0MPyQjUjHCx7LaFve3GiJDksd1toaTJauOOyhAp+Mxes3aBjag//2OV8+0vYyCVhOVEx3VHURDpuKcN0QOpi2c/8ZyKP7+tLkurfRB1/nI92up7q3zQdcGI3ncu3cxX7ZtG/NISOnI8UH8rjwhptZ++Ay/HPf34DLkYVkFqprUaOfXWCHaqQZNniD9uzyj+mkfMx5YfjvcFRKEI+vipVv+upkDI7IBnAcLjQ2Y/XdPi1N46uv4N/357NidA8Gd0hkZ5mVpZ/vZ9s2jU8+kcCsZ+xz50JCnFgPGAzBjo0ZGbIApKZCTY3QNHa7eMkkJgpVk57ubUxCgxqnyqR3fyclSaGsQmNExyQ+2lPBjZMhNQ0q3EqZtu7TpqMtsLvRXA27L0ItEt7At4t/zphH+649+eeM2axechoo7XHYdrmdFp9m4vT5dOndl4ycjnz06lpefuRJxMZ3X8Ax9yMUSnHA57qu29/TEK5COlD3AdFI4fZu9AzeYBLqSQ/mu376kTXLFmE0d8Zh24mmurDE9MRh24nQOQOBbIymg/x56DD+99lm0de7FjX52fnSMo0tVvoGbZvWh9W1N/PXmBlEKza/7QKplFA8/hlbY6nKraX2z1biv4pp9H0cSjTWL0Xffs8ezePX4lLh/R1l/L1vBidkx5PbKZGZMytITPAWPAsLISZGMm+TAv3+JDx5erpk38OGwR13eJuOZs2SOakOh1cGuW0b3DoDVE32q66EJ78txBwFMQka5dXw0Z4Klozsyp5yK+VWF916R2M2KlRYnWFH6bV1n9aPtifhg+Zq2HXoi8Rj807DYc9ECpsPAgOIjr2Crr368Nk7b7Jm6SKM5o447XuYMHUGff4y0JPl6jTGwJGjefmRhxFu/BaEenGL9ZRYTKbbUZRUHPbBGIwdUV15iKdhCRJ4uyNZtAFpUNJf2Scjqp2e7p/7oyjtee6Be9j6/gcYzR2x1uwAtnpqDjCcuurbkEapNciish+X08GPXxdiMFr46z9G0OekwXTp1a9Jz05omQmezL2xxUo9aG+0tueNurF0MO5jduJ9YbcPx+MP/S4LY4WB6iG1R1xgb2zGmhlnJr9I9fivewuUpfy1u3jQfJJXyfTpUhz1LXjecAOMHQtvroPvvpPA7ZvNl5d7aZn588GoQI7P9KYBAyAzS8b1nXGGBPrZs4KnK733eykb91WSngb7t2skxILVBpNOCK2Oaes+rR9tTyMATdWwB2Lo6PPpfHxvZl94Hi7X2+gDLZwOmXkaWKh9dUUuw9dv8Gtwcjn2+IzMOxOhT9YiwTkJs/ly5jz6DCaz2TM/9aevPuf5h5ehqQpi/3sAoXe6ApfgLaJeAqxGCrt5wCzs1h1sersa0HDYJwAv4U/xpAGXInJKA1I3kHZ6a80HwNO8+fQ83n9pE6r7jcdXVdQYKakvLdOUYmVu9CdcGPMij1Zfz9nR6+lv+T7kdqG6VDspsM+h0v6LGCqH16BGqxisR045qr6MNZQEMCnaxOguKXx6sIw092PXvWR0XjorQ6FzZ42cnOCCZ7duEJcAsTFeT3UQGqagQGiWgwfBbIQzOiexIa8ySF55kntKZ3S0dLf6niM5Gd7fXcHyR7zKm+g4sDrg4S/z6ZIc7SeP9H0ObQE9NNqeSgvDN3glJKeiaiqiGe8C7MblclBScCCk2djun7cHBfx1T5zmtvvVdeVX4plrqmRx76SrPAG0sqyELyvfQ1M14Am8RdIhgBlR3exHFoerCHR5FFXN3XhNyYwE0zkvhNh3CKKQuQ/Y6vbA8VcVffTKc55B2qpzf0RS0vqGdUSCu5Lu5hPbcKaV38/6jLOxKMHFtfp4/LiNcRgqDWhHTkz3IFTGGk4CuGlvBe/tLicpVUbd3XKLGIb5ZvmFxRpWK56Rer5doi++KBa/Npv/d/v2wbx5wq3PnCnHvHFyBaoKk2+QwF98EFDluMnJMm6vsNDfl6aiAtp3CD8rddbHuyLStR8qtEa9fOu4ylaCQB386AmXoKntgc+QwmkXNHUItdWVIQu1gE/AFw9Bo6kD511+Dm886daVO1RU535U9VEcNoAkHp9/pY+/Sy0SxJchnaOPIJYDM5DpSsuAyxDTMd9svD3S1KT/nIVo3gcj2f5upFDbnmC9fTZigeBf3NVVRV989B5PLZwPHIfTkQfM5vH5d0QkJW1OcE8yVLIoeTZXlK7imZrLuCb+iaBt6uXxdxuJ3t1yBl8tDd+MNVxBtUtydJClwI2TwWiASSd4eWm9wSkuTmPyZJEbFhb7e8bceKMMzkhOlkA9fjxs2iSNTsnJck0dO8G554rj45VXSSPUnNkw9SaF2FiN8ioxNZs9W/YpL4crr4TnngutvOnUCS68EB564I+RM7ZWvXxbYG8hhNLBr3/uNKRAmY/YA8joh9j4RL9CrdO5lzFXXUNauxx3wPd6CFprd5KQkubRlddUVrB4yjSEXukI5GG3x7DqvrtxueYhxVHf8Xu5iBwy3b39AGRi08UEF2L3+1xnIUK1pCIBHqAc6dfcTWAmHxWzHFvdXgIXq+jYOFYvXUhgM5TBmBORHTI0L7ifEf0RK1Ku58zoD8JuUx+Pr5k0av5sJebnKIw1R2Dq7ka4guqvbt92389zMhUu7d7ez5/Fb4iHycCvJXW8pRR4PGP27BGbgMRE8W9XFDj5ZBnuoWfjutxx5UoJ6EuWwKRJkJOlMDgpjdd/O+jnLTN1qmjd+/cXHb0+9MOvdlAoNM4fMUyjNevlj+yra0UIOWnI3BnV9SuqmotOxRiNisefvd+gU/jolbWse/Ix3n72fd54ciVDR49m4xvz8AbCjTy7+Hx6n3gy3fsO4JdtX6K6qny+vwu0pbhcHZChHYn4Z9OpSMC+EcjDYByH6ipF/GlOQwqt+91/Xoxo6SuQISDv4m2+Px+RY56D7hFvsnRBUQqYOGMeXXv1YdfPP7Jmqb+qyFpbg9HcJUj66XTsatawjsbg3Jj/A6BajSNKsWFWnEHbhOPx7e0dFEwrIeOJZJI2HLlGVeEKqsf1jeHp7/0/LzoI6X8yh21wqrA6SY0xUeSmZdLSgouqN98strsWi9AlaWky21RVhe554QXh55cvB6dTo6ziIDFx+HH8WVli2bt4gUJRicZ53VNQFJhyYxnJqXK8W26RheOPkDO25mlNR/bVtSKEkjiqrjyumD2PZ5fei8FQjaqqXDfPXyf+xlMrcdg/dQe+7/jv+lOJiumBrc7XVbEdt100juvnL+R/n21E6JD+wEqkIzWQK9+IXqwVXjwKCcYxaFoZJ50+kq8+Xo8UQ/OQAJ7rs/984FF8R+hBLAZjBedeejV9ThpMWrscPxMwgO59BzDw9FF+BdLKshJUp38mD79x2a1zmzWso7EoU5M5q/gdLop9gakJD0a8n2WPGfMBE9VD647owB6uoNoxKcrzeVqazC1NSdS49aNdGBTIzjIE8fE69YAGN02GtBSFpCQtqKh67rnw2CMw79RObC+q4bWDJSSnSVC//37vQI9VqyAmXgqsEybArbcKH79vH/yzbwYOVWVdSSn/q62goEhDVWHgQNHCr10r213VP/OwB9PWrJdvC+wthHA6+KGjz+fkkaNDqkFCZfmKkoOt7nckOF+HuD72x+n4jkfuPAXV5UCKmhsR3vw4gicijUZ49b1I5v0pevavqaPdQf1bJAO/Au9EJp1r74zQR4ELhpFOPXuHnLLk+xx879H3uRiMHXE59zDx1nmMDGESFgnC2Q80hBRDOX+xfM1DVVMYFf0evc0/R7SfgkL8lhjKxlXhTHZhKv/jrQTCIZwEcFjnJLokRzPzo10sWgRdukhWLUVKNYiP96Uept6kMKFbO1Z8W+AZi7djB+TthccfhRv+kk37RAtmo0K/zDju/u9esrK9w7Gff54g+uW++0RTdXGfDEZ0TWLyezvcNQDNUwO47DL5r6BAMnrdBuFwojXr5Y/8K2xFCKeDDyehDJXlO+x7kYB9HoEFTtWV5f7OiATv9kjGHahcSUBUMbuA2/H1VBcJ5D5kLN9Yggdp70fkkLrdAegLhuo6K+KiZyTPpSkI1Lk3Bv9KvJPNtlOYXr6MN9PPx6QEWxOEQsKWWMrGV1E9uJbkdxMafd7DiXASQKtTJStDITpa47ffxK43sCU/FB/fLlMhK95CbqdEJk+uICNdlC4nZcUxoV8mW/ZVsuLbfLIzJfMf2C6OLQdq2LFDGpXS04OHbJSVQbQJXvn1IA5VDTpnalrAQOwSjWq7K2zD0qFUrbRWvXzruMojEOE02Y3RwSempDFx+iyeWXIqJnMnnI69aCTjctwE9EOyad+gm4/Y7Ka4/8wHbkN8ZTog3a0zEHqmxv15IYGe6l4541ikUUk3Ccun78CT+OXbmTgdroBzlwJrMBjbR1z0DLzXlugP0NGUzD3VWMaCpNu5vuwxHq2+nhsTlke0nyXfTNQuM3W9bEd8YA+HneVWDhRrLF0qBUlVDRyjF5qPLyzWiO5r4JO8Sr/mpDmza/hf8W6SUjUUI0y4VKVzZ5gyuYaURJEtpqZKMTVQPqlpsHINlJRoTL2pFA3/c1aUwr/vhxfXGNhfoGJQYM2uAxR+EaxKORyqldaol29dV3uEoD5738Y04Xz2zpusXnYfJks37NbfURQDLmccQqOMRxqScvHy3E6kIagL0k16G3AvEuh3I92t1wCvAeciPjA24K8E+8lkuM9jRWSMewEjO36oRDGY6DtwAD98EThCb2Gji56HCtVlE/h2M40O7ufErOecurf53D6IydpylAhtYLIXp2OsPHJVMfWhwurk2e+L/IqfkybBlBshx4dj9+XjfQOlnu0PGCBZdXm56Kx8JZRTp8J//iOZf3EJjPubxiuvQFyct7haWirql0svFRVNcrK8EQxKTOWWKaWec046sZ3HjXJp0X73edQgVUprVq0cahzbd98E1GfvG9g1Wl8TTshpS0FDNkxI4C0C6kBRMJnGYDR1xlZXg3eoxgH8C6A7Ee35b+5j6POCFgMz8WbgdcA7QF/P+fXmol//l4vJbMTpuBZ5O7AAv3H2P69qqUfZbDSVlrk/eRrRihVFaXiIhw5T5ZHLrTeE93aUkZTqX/zslK0wsVt74i3GID4+kHqosDr9iohffSUDMQK7RydNAlSNi3pnsPalYs9Csm0bzJkjnPnTT0M/t9uE/kYw6sQURvVICaI74i1G2mWGV6WEGvzdWlQrhxqtMwX5AxHO3te3a7Su+lvsto08Pv8OKstKPPtWlpWw44dtnqzee5zdBE5bEmpkJZItLwaiQXsXRVG46Ka/YbZ0QwL4E0jj0WiMpp7IgjAPeAUJ6rrN71b3539CKJoVSMCPC3l+k6kTfxk+ApiGNDqdDTh5/6WNTDl7BJ+9+2bQs/G9v8OJUJa/9SHWUIdB0Xi2OpFTCgdzZ0kxIwoLeLO2pt79ykdXsX9OccTnOfGT6kZdV2Og295WWIOlm4HbrfuthIoKf1vcwmLxZe+ZFhMUBJOiTZ6xejqvLZm8wjWXG/j3/TLlyPd4lZWwcCEYFOicHEXHdl5b3QEDhJZ56imIjZbmpCsuVbhliuIpRiZFm4KuxVeV4r1uzWPnu7O8jryC0N9H+nyOVhzby1oTEM7eFwhpE6Dz0YH0zcTps3D6TVvaRTCfnu4+1sUIbx6HydyFpLQMHPY97m3KgGeRIF2I0ZyOyzETaUIKtPnNAS5EFoJ8pFBag2TsvuffiN32O998uodA6wBrzT7gtqAianOnTzUXjeXcS1wu5lfOBv7OC9qfsfFr2CEeHrgU6vrasHVwELXvj5O8NYZXLqpxkJ1pYMKlqsfZMW8v/O341EZPJ/LN5L8rrOHmmwpITtWoqhJd+4ABIp8EKCgKsPgthrvuglNPlQz+9tkai0d2DekBo6MhT5zV24v9xvjpssjvimpaZbdoS6ItsDcS4WSNXXr1C+vnHoq+Wb0sl7MmXMKbq3Qe24E0DGViMBagupwIbSIGXb6DMGLjEzFHZeGwDUc6W6XTVMbX6Tr2gYRSzJgsyzCbX8Xl3Evu2AlsXHcBRlMnrHVWNHUwMvu0HE3NwOG04L8w6NYEN/l1jjZ2+lRz5sqGQ2NpmTyXi57M4gDncCVP8Smn0UnR/CYuBSL+8xgOXlpO9ZBaol7+43xLGsMr61lv584ysk682PG4Ojb2+J5zKKBpGsVFcN9ir+9LYbFGUZYdl6p5/NXLSyElSYI6yLY57QxYnWqD9xtOlaI3D02YoHnG+C1eIAO8l32x/5jn3Y+dO21BhJPvhfNz3/HDtpDZfJ+TB/PO2tU47DMQw64fMJrORTGYUF1f4su3G4wJGI1juXbuQrr06odCBVI4fRTf4GuJ6oaqno/Z0g1rrYqmeW1+//qPCVxw7RS/677g2ins/nk79914rfsYFcBWVFXn/X0Xhj3u6+yAw7bDz2K4vrcVIKTH+6HI7CPN3DsajRyggOnczB2s5jZuYq/2UMghHjpMlUZifoiiakgtqS8nhhybd6jR2G7IwKw3v0hlbI/wi2kkx9eD/0P/EauBO+8Uq4HKMoVL+2WyensRDy+XgulXX8G/l8lIvKY2+oRSpQQ2D5WUwMFS+a61dou2JJp1p4qiLEEE13ZkcvMVmqY1fZ5YK0Io+V64gB+OvunSqx/XzVvIo3Mn4XRkAPloqorRqPPdYgQGWRhNJsRj3dfvfTYOe+Cc1APc+8Ibnq7QqvJSft/+LT36nUD7rj1D8t+b33kDTVMR6kbDu1CsQJwbs5Fi6wqEwvkNTfMGtYamT+k0jcHUPsjjvbFzZRtCpGoZ3fzr9vLnSOAfLGEhcxM2kWYsqne/hC2xFF1bhq2bg+idXoOwSIuwzUVTuiH1rPf9HWWsKyrl88oy3nyvNCRFEcnxfYN/9+5w4olw0ySFGYOkGOsbWM84QwqmtlpRx2RnKhQf1BjbI7VZzyEcTdMtJZrCL1pnt2hLorlL2AfAbZqmORVFuQ/R381q/mW1PvjSC937DvD7rr7pTP0GnYKiKOiTjFT1B+y2s/E1AoNCHLYHgUGeQKgvIh+9upZ1T+Zi8jlu+649Pddkra3hhFNHhuT5h48dx8Z1r+OwpSGj9G5Ffn16gO6NdK72Q4ZrLEDonQeJilnuycjruz9/msaGyDHDZ/bhnmljAn+kwV03/9pmv523rDMYH2evd3uAuC9jSOxux1DnXdhCTWA6PzYu4uttDJrTDfnG76V+HZ46RQH4Nfjox09PlaB4ef+MsEVNPVuuqPQOyQ5cGCorYfVq2L0bZs/UMJuUeheXSBGOpmmt3aItiWbdraZp7/v8uBX4W/Mup3UiksJhuGy++ECeez6q3mKfi2KIRVPnEeiICD/7BcLElDTGXX0TA0eO9svKQ13TP2fMZs3SRT48+EY+ePHsEOe4D8nSuyEyyvmIuZgTmIiM9/sBh30n0T7Bq77787ci9uf9w82VbW4xtrpsAmMXPsu6OfW/QKYZjYyMKWVkzJyIjmusNZD5lJefDjeBqd4ibDPRlG7IcBTLezvKePP30qBCY61T5dnvi8hpp7D6h2JizUZPAG5ocdG/y0iDA0Uat84UOWSXLjJaINTi0tTAG4qmieT5tEaP9cagJe/oSqRvPSQURbkWuBYgvV37FjztH4vGFA5D0Tf+NEY28CqaWgX0wr9w2Qn4ICgQ+gZAp/1uxl59HQNHjg4u1i45DaO5o0+A3eM+n+85OiPyRw3xbT8B+BhwYDR2w+Wai8G4BNVVjcHQndsvHu8XcBu+v/7IG8FgomN7orryQs5GbWwxNhym93+Hbzc/H7FaZoezG7PK7+P+5Gl0MuWF3U5Dw9bDjqHGQN4eLeQEpvqKsC2BxnZDhqJYCoo01hWV8ODDBHm4r95e5NeAFBiA6wue+nc7y6wsObiPzp3l81D695biv8M5VYZCa/VYbwwafJqKonyItCYG4nZN095wb3M7ktI9F+44mqY9DjwO0K2P/s+g9SOSwmF90GmMFXeegsulIpJEIxJ4fbnzXzFbbuDauQv9CpLeAPgTMImXH3mN11auwGgI1Np3xmnfhZfi6YDw5XrT0kbgR2R9NuD9lU8CtuBy6Y6Vg4G12G1jiSTghqJpJk6f6xnWHWq/5j5TX0SauQPEKHX84OjLreVLeD5tAgYl9F9TLUpj/20HSdgcS8eViWEnMB1JCJVlj+2ZytaKMrp3F3VKfZ4xoQJwfcEzKdrECdnxTDoh269wi9b0Imo4NCZQHyvdqg3eiaZpZ9T3vaIolyH96yM1TTtqAnakaKhwGAn6DToFg8mMy7URb3gYiq8HzPmXX8XZE6/28Nb60A0JgNnubWV/l2MjLs72uybVlcd5V1zD64/PI9i18UFED68HexU4BVlkUgmetHQZskafjqKks/vn7SEdH/Xr7DfoFM+gkEj48pZ4pr6Y3v8dxi48q8HgnmPM587EfzGrYjHP1V7CxLg1Ibcz2AzEfRNN9cA6uj6THH4C0xGGwCwb4I33SiP2jGlKAA6lf29J/ruxgbo1e6w3Bs1VxYxG3q2Ha5pW2zKX1LpQX+EwHAKLgsUH8jCZO+Ow+QbQdliiVFR1F5fdOpeRf7sECKRediFr6Qf4j6vLxWzJBE7DZO4imvUx43jr6ZUEe8boDpFf4D91yQVcDcwl2P1xEpLZm7FZM1g27SauC+DAm8ORN+WZNoRIaZkJsc/zdt25LKi8nRFRG+hg2h9yu4TPYqkeWkdtPyvn/y/8BKYjDYFZdkMe7i0RgH3P2dJuiaECdWY6YQN1a/ZYbwyU5iTZiqL8jkxx0DV0WzVNu76h/br16a8teG59k897JCJSBUeogNdv0ClMOXuEUCruAGqOymX6/Q97pi1VlpWw++ftLLtlMg77p57tjMahKEYTTrsD35F4lqhcFqx9FWttDdGxcdx+8XjsttcQczFfl8fBCO2y0+cqTwSKMBhKOO28cWx8Yx3QE/GbGY2YjBmCzvfQ+g2eaw28H9/vW/qZNhYNNTHlOTtwRvGHXBDzGvcmhy6qakaNXSsOEPdNDFmPhpfufTP8yB3OoSNcITHU50da0bHC6mTyezvcGbt3APZV/TMZFUZSuWlPBY9ta50c+5jnf/5a07STGtquuaqYHs3Z/2hCJLa04YqCD63fEDJD1ekNfTFA6eDWrX+OBMz+WKJ7cPPiW9nxw3dBsseE5FSstTWUFBzAYGoPtjhgEULbpGE0FXLCaafz1ccf45+V7wZUDKYoBv9fGpmoAAAeT0lEQVT1HLZ88B222ieAeOBUJJN/l1CyRYBv//sRBlMnP47cYOzYaI68pa1+dYxdmFwvLdPRtI/n0ybQ1/xD2G0Ul0L8FzHU9rehKRqKdviblVoK4bjywM8PRdGxuQtFUrSJiX0zmTy5kA4doLhYzMZWrylmcIfEkMdsrR7rjcHRd0dHMOorCoaTC/otBn5ZNsAgT6NT/yHDGTn+Ys/+27duZsrZIzCaO2Or+x3V5UI05HkI1fJ/mCw9+G7zZ/T+y4n89LXXk12y8Scwm+8FQHPp4/WqESXNGkDBdzFwOvey+6cf+NfVl/o0Inm/t9b+xu6ffgjS+P8RiISWOdHyLQBVajxWLZoM48GgbdJeTCL9GUOrDuqR4lAUHVtqoeiWEk1OhsKMGRrt2om08uP36ufNW6PHemPQ5u54GOFfFITAomBiShrd+w4IGp9nMHXCnxfvCdyE2XKaH/es7w/4OE2+j+oyIwXTbQgN8w7wArbap7HbXuPXbf/DYDIgVMsyhJbp7Vk0rp17D5aoXKJiLgd+R2SRK5DM/0RgCGdNuITVy+7DbtuIteZ7xFNmINDHvd08Vi+777A7P4aDqGWS693GqRkZc/ANppcvIxRjaawyYnAc/UEdfLls+dm36NgU+C4UK1epPPCQxmPbCprkxpgZZ+ZgKZjNEtQDXSCPRbQF9sMIvShoicolJm4AlqjcBouCshjsxncxgH1Yorsx/YHlIQuSDVsCJyPTma4HxuFy2VCda4C7gNnAEIymYX7dsdPuf5hbls5hwtSZiA1wb+BnYAZmi5k+Jw/2OeeLwHJEe38AoX9m+tE1RwJELRM+uJsUF/+MXcMG2+m8Uhe6966mv5W9CwtxxTRsaNWa0ZCFbmPRmIWiIQveQFthXzvgYxXH7p3/QWjs/M/ElDQm3jqHpxYMxlvAnIWmLiStXU7IffzfDLoQaMkL5UgG/xMS3Dsh1sDtEA19DeCi36BTQhZ7r7x9njQ8mTq7m4wW+rhbbiR4DN8IoGezJIuHCg1JIS+PW8X/Wc9hfsVchkVtop2x0O97Q62CvbODmpPqSNwUbCOQPeE18p+/4JBc++FESw92jlSdEildcyzw5o1Bs1QxTcXRqIo51Pjoled4ZskCFCUHh30v5qgsFCrCygg/e/dNHp9/B0ZTJxm7ZzBitnTFYd+JRgdcjk+QhcKrsIHhiGPkLVii2zNt2Xy3CucRxNUx36NuAYIWp8/efZNH587G6cgGfvG5muMwmQu4fv6iw+rR3hjUp5TZ5ezCmUUfMCxqE0+lXuk3Tk9DY88DBVjyTeQszgjaN//R91tFYI+0iNmSSpmG1CmhFC+3TFFYPqr7MRu4D4sqpg2HDyP/dgm9/jKQ2y4aA6zHYculvs7PwDcDkECsSx9dvIrMPdUpmp8Qk85HAQN2617ef3G1W4WzDJmi9IiHTgmsBejn7Hx8b+ZMGIfD7i2cmi1FLHz+DY+PDRw6KWNTsentLSz7LnTm3tW0m5mJi/nYejq1WixxirdlQ0Ehfmss5edU4UpwYaw6cjXs4dCYImZLKmUayrKb00x0pMkyDzeOvTtuxbDW1mCO6o7Tkev+pP5W+0C5oK4xH3PVNbz62HRUF3g9asQ6wJu9n8Y3n36CV1opjUtOh1ovndK+a0+um7cwQLq50C+o/9HTlsJhev93EAO0YFwd9wTXxK0MOfw6YUsM5edXUT2wjqSPjnzdui+ao3ZpzL7hAm196pSmNBNVWJ1iT/xbKe0yW59OvaXQFthbEZrbau8bUI1GC6paB1ouMhA70DqgM8LF+36WytirxzeYYddXR2gpg69DhU1vbwlJy+i+MfmudrxeO45J8Ss8Qd6y10zSB3GY81vfP6fmZMWR7tvYrN53EWgMr79pbwUrvsnHpcJ/lnNUe8E0hDZVTCtCU1Q1Ovbv+o3H5s/xDNt22D/BZIrCZHZiidIQ9Yqv8mYvUOT3mTmqlJHjL45oaHUo6SaEHwZ+JKllNr29hW83Twn53Rt1Y7i3ag5vWc/zfKagkLEqhdgfow/XJbYYmqN2iWTfxsoaN+2tYPJ7O3j0lzwmvycHXj6qO9cf35Hlo7o3aO41dRp07BTaQfJYwrGzhB0laKyqBiRTf3SeXtT0BlSzpSs3L76VuMQkdv38I88uHuaZ5GQ0KvQ5eQjfb/WO1hsxdgLbt24O8nnv2qtPxNfS0gZfhwrhhnVcHfcEb9edy50V/+IUy2bSjKWe7xzpTlyJqt9kpSMdzVG7RLJvY94IwlE7y0d1p2daTL3Xop/npJM0Hn645R0kWxvaAnsrRGNa7XXqw+l4E/GJCR7Pp2fXA08fxe6ftwOQ1i6H2y8eD6xHPNpr+Pi18/notZdxOd4Ed/H2qQWDiY7rjurc7+HK6yuMHgqDr0OF6rIJgH9gNykulibP4Jzi/+OOintYkXqD57uCKfIG0/GurMN5mc1Gc6SCDe3bGJ68ObSQfp6SErj5Zpg61TuH9foTjj1N+7F1t8cgvDYGucAj6D4xZkuRn7c7SNDV/Wm8A7hz3d++iNPhQrL38e5j/QPoibXmCSCKx+fnUlddxepl9zVpmtSRiE1vbyE+xd9+oJf5F25OeJAlVTMZU/cGo2PeAyB+aywll1Rgz3JgKWxdGWJzWuwb8mWP9I0g0kUgVCE28DyaS2VEWhqjBqUcc0Ed2gL7UQ9/6uMfQBYm8/lB8sP69wulmhkBZCENU12ADAzGjjyzZAFOx3+bNE3qSEWozH1S/AocmpnBUVs9n8VvjaHkkgqqh9SRuq51BfZDiUjfCCJZBOorxLY1KXlx7N75MYLQ1MeieoN64H6Kko7Nmoa/QiYNGIV72iFC7ezBZOmM09H8yUdHGgJ17mbFyfTE+wFwaQaMioq51ET0zxaqhtaSsi4BhWPDRyYSRPpGUF9wjkReebSbe0WKNlXMUQxdvaJPMJrz6D08tH5DxJrxoaPP56H1G7hl2VzMUSX4KmSMpgIMRgti39sFo3EoE2+dg+rcTziTs9aOUN4y+a52nHfwLd63ngnIAA5HOyfODNcfcYlHBZKiTfRMi6mnYUl+PlYVL5GgLbAfpfjsnTeZcvYIFk66kylnj2D755tDyg8bgs67X+cjszRH5YKmoro2A78BWzCYLAw8fVST5ZitBdLE5EWaoQSnZuK28nspV5NI2BxL18nZmIuPvayxIbOu5qKljciOZhx7f/uOARyKJiDd4VHHg7OWUlftpVxMDfjKH03wpWUsioNlydM57+BbzK+YywOGaWD9o6/w8ONQDOEIREsbkR3NaHsiRyHqG+jRlEAbaAEwcfqserXorakw2lT42g/8ybKdG+If4eHqKZwb8zbDurxH0VVlpL9wbLSxH4ohHOHQ6gukmobRqWKxqxhUjZoE6XnI2ldFbI0Di92Fya5isbuojTPzS38xljvlwz3YLZH7ELWyp9KGSNDcJiBfHTrAY/PniMOjTRweVy/L5Z8zZrNm6ZGvRT+U8M3cb054kPeso3i65gpyKz7E1sNO1dA6sq//K/mtYO5pc9Ac/XlT8EcXSBWXhtnhwuRQqXUH5tSiWhIrbJjsKmaHC7PdhWZQ+P6kdgCcsOUAmQdqMDtcGNyGupWJFjae0w2AHj+VknawDgCH2YDDYkDRYj3nPJgVi8NshP3VEV1jW2A/CtGcJqDA7PyE04aFdHjs2qsPD63fcFRTLpHA1899VerlZBqLMNYZiP1fNNWDaklfc/Rn7U0x6/pDoWmYHO6sONYMBoXEMitJpVbMDhWzXQKz2aHy7eBsUBSO/76YTjsqMNtdmFwSmZ1GhfUXHg9A5x3ldNxdCYDLoOCwGKj14f7LU6Nxmg04LEZ34DZijfGG369ObY9qUHCYDWAIVlP98ie3JfS3RRHdYltgP0rRFK47FDf/+QeDke7TXAIdHn0plyPNhvdwwhvc9wEyJ7ViUwqmk7+nrrcNSPhjL/AQ47Bz35qGwaVhdqg4LAZUo4HYajspB+sw21VPUDbbXfzcPwNbjImOO8s5bnuJ5zs9dL43tge2GBPZ+6o4frt0DmuAwyLB1+jUcJkVauItFGXHSWC2GHCY5U80DRSFHwdk8uOATM/1BGLX8an13pItpmWfVVtgP4rRWK47FDcvnaZxPj8HOzweqTa8hxO+nPv1ZY+y98McVk06nuohdTIm9ihHo7lvVQKzalRwmQxYrE7SimolMDtcngC9u2cKVclRpBfU8KevCj3fGVXJmjed0YmyjFjSiuo44fN8z+GdRgWHxciOXqnYYkzYok2UZsR4smU9QDtNEuJ3HZfC3m7JOMwGnGYDgf7M+7omsa9r+Levlg7MzcWRdTVt+EMRipuXztIa9xZeh0cdR7oN7+GEzrnfNWMZ4w6+zlcvX8Bo28d/9GUdGmgaRqcGCrhMBoxOleNK6uhrVzHrmbPDRUGHBEoyY4mrtHHS5gPebNohM2K/HpLN/i5JxFfaOXnzAc/hVQUcZiMF7eOpSo7CYTFSmRLlyZR1SkOnOwo6xPNRejdPNq0Z/QNzUU48RTnhax32KBNEHYLn9AehLbC3wYNQ3Hzu2AlsXHdBWK6+pRU4rR3T+7/DiZYhXB33BDOefoUOaf8g5q/fNbzjHwBF1TCoGi6TUAoZBbXuwOvNmMvSYyjokIDR4WLQR3sx2lzEOFUsDhWDBj//KZ1f+6VjtrsY9Ol+v+M7TAaqEyyUZMbiMkkQdniCswToilSxOq5IjWbDWV0837lMil/WXJEazdentA97L3oW3gZBW2Bvgx9CcfMXXDslLH/eWmx4Dyc2vb2FGeeM4APrmdzluJN7My7AVHwIgo6ba1ZNwummHKwjqs7pF5hr483kdZNu2UEb84ipdXi+M7k09nZNYtvgbPn+0zwMqvfwqgF2aqkUdEjg0wNVWCpsWKOhUIWuOXG0y4ilNEOUG7ZoE5/8tbMnwDrNBjSfIqA11syXp3UIeysuk4Gq5NbnZ3+koi2wtyEIoUbqhcu+W5MN7+HEV/+3gaVnTuH3y10kj9pB9eoe4AwuqikuzUMbJJTb3IHXW/xzmgyewlv/LwtILvHSHGaHSklGDJ+N7AzAgK35JFTZPcfWgPwO8Z7A7jAbcCVYPIHXbjF6MmYUhf+O7CzKDTcPrRola66wOlmxrZDjHhfVS9EOGDelluUDsz1cumZQqGjAM70Nhw8tEtgVRZkBLAEyNE072BLHbEPrwbHQbRoWqgoGCdhx+/YQvz8PS1UF5qpKLBP7MPCzB/j9XBVTp2q6vmknK7/GK6ezq9iijXw4pgcAfbYVkZVf43f4yqQoT2BXFSnSVScKjWG3GD0NLgDfDM1BU/AE5sAi4Df1UBkA5emhA/Ph1qm3oflo9m9FUZSOwJnILLU2HKNotd2mmrtbRFGIPlhEfN5uLFWVWCorMFf/f3t3Hh9Vee9x/PPLzGQhmUkiBNCQhKCgYEByG+hVRFGQTRrq0iou1fry2muxxZcL2lK1btjqFSgul1K9eq9Yl1JQXFBRKSoqLgjILkEgGJRgkplJMmFmkuf+McOQMWERh5yZye/9D8w5J2d+eUK+POc5zzwn9OfGX/yK5vQMihc9T/HL80P7vB5SvR4cDV6e+7AC43Bw0lNz6feP/4s6fTA9lY31qVQek09hy06abYIvOy1yA3Bvq2DccEoem0u64U9NIRi+Sdh66tza8IddDiTS+46xhJunrmLSY58JTAVejMG5VBxKlDnqDq8H546tocD1uEMB7XWz7dzz8eX1pOcHyzjpqbmRwE71enB4Pbw6/y3qC4vp/eoCSmfd2+a8WydehC89g5RgEGlupuHYfAL9BuB3uvA7s5GWZgwOvrjoSnaMnkDAmRPe5yKYmUVgxz0UlzzJnY6ZXH72Q+1UHuLJjc8xZl2jJfH8oJ+MiJQDXxljVoscfO1pEbmG8OLd3Xoe/JJQxY+OnKNua/Lh3PElDq87ErypXg+7Tj0TT5++5GzewMBH748E9r5e83v3z+Hr00bQ46PlDL/5mjbn3TOwFF9eT1ICARz1HgJZLhqOK8DvzCbgyiaYEboBWDlyPHWtAtvvzCbgdGHsoV+TivMvoeL8S9qcfx9Pn75A23Xuu+RPILVhLrtdeWyoLqV/3mexabAOlPBrtHQyh/zpiMibQHvXgNOA3wOjD+eNjDFzgbkAfQYMMt+jRmWR7ztHXZqbQ0MZHjepXnckfGv6D6SmpJT0b6v50Z9vC/eUw+Fd72H15FuouOBSnNu3Mm7S2Dbn/fCPD+Lp0xdpaSbzm134nS68BcUEwr3ixh6hWR17TvkRy2Y9EQpmV3Z4fw7N6aGecNUZo6g6Y9QBv9+G/EIa8gtj0natBWyDybuhNxs3n8qWlDJmjT2PNPvemL/P0Wb1Gi3q8B3yp2SMafc3QUQGAsXAvt56L2CliAw1xnwd0yrVUdHeEEtmVSWp7rpQ+K5fxVVksZlq3gaEEp4MGspuuJocCI81u9k68SI+nzwVe2MDE84f0eZ91v7HFGpKSjEpKWRXbMbvdLE3tyveoj74s1x4eocWQqrPL+TdB+ZGAtvvyg4PZ4Q+kl97UgmvPfPaAb+fpm7dDxrclhFhzePvct2Nt3H70idYsOFqJg18xOqqVBI74v9+jTGfA933vRaRbUCZzoqxVvq31aTW1USGMVI9bvxZTqrODD3hZ/DMe8jauR3f9q00fFlBLjbeEXj/npmcNracMZeOJ81dFznfhcA8ZvA2IzGsZVCLhxxfI805x+A+vgd+p4u6fgMACGQ5ef/e2fhdOfizWvWas0PT7fbmduXVfx74k5jBLCc7R447eo1jJeOj7O4aZjw7jh67aqyuRiU5va6KMw6vh7S6mv1jyB43GEPl6J8AcOK8uXRdt7rVzAw3jT3zWfrffwfgjClX0nV99Ccdq08piwR77qZ1OKq/Zvu2bdSaYXxOER+ZfP525x8o+fEwPp72J1psNgLObPyubD74dAUP/2UGGY7BNAd3MOeOhw48xi7C9nHnHb3GSWSSgb15IwOHVdK4qIhgix1jBIdNH+umYi9mwW6M6R2rcyUyW5OPtLrayDBFar0Hh9fLtgkXAFC0eCE9P3xn/81BjxtMC4v/8RYAQ++5hcIlL0ed09eteyTYczet55j1ayLDFA3H5uMtLI4cu/ZXN2DzNbYazsjB79r/nM6lc56hYt0qpl97G776ZZHtGfbFVFdVUjnq3Kj37t9vAPeNLU+IWTHxrskxEWfPBwikpzD1heco7fkevxg80+qyVBLSHvt3SCAQvvHn2R/OXjdVw0cR7JJJjxXvUrjklXCPev9xr897mYAzm5K5sxjw5KNtzls5ajzN6Rlkb9lEj48/iASzt6CIgDM7svznlgsu46vhIyMzMvyuUM95nw/vnnXQ+quGjzzk9/h9lwFI2DnqccbnKMe59wF29uhPn9wNLNx4FacWvEHfruusLk0lmeQL9pYWHA31kWGKUPDWseeUMpq65pGzeT3HL3wmMsyRGp7TvPy+h3H37U+fRc8z9N5b25z2lflv4enTD+f2reQveyPcI85mb3Yu3oLeSHNokY3Ks8fiLegd2e93ugg4XTSnhpaOW/ObW1nzm7bn3+ebocOOTru0ossAWKPZ1hu/7RQGjNtM3hd/ZuWu03loxXQeHHOhDsmomIrLYLc1+aKC2eH14Ck+gYb8QjK+2cWJf3+sVY86dJNwzeSb2TXsLHp8vJyzr20713jZX56kavhIunyzi6LFC0NjyOHgdRefgLGFmqK6dAif3HJ3aF9kylw29b1C0+C2/PwKtvz8igPWXlNSSk1J6dFpmBjq1MsAWKgx9UrsLV+QlfYWk4fcwd3vzOH5dddy6aDZVpemkogY0/FTyk/u1t28cPbY/b1mr4eK8yax9acXk7lzO+Xlp7f5mk+m3sUXF/8SV8Umxlz+k1ZzlbPxZ7nYePk17B5yGhm7d1H4xksEsvZNlwsFdH2vIoKZyf3sSZU4HlwzjttfDzLzgz+xw92XB0ZfhD0laHVZKs5NfGbjp8aYskMdZ0mwl4mY5Tm5rabEZbO1/GdsH3ceNl8j/Z59Yv/NP2dov7dXEf7cgz9eSqmEYIKkNn/E2zfWMbzHX3GkBHQoRh2Www12S4ZiavoPZMHTr7a7rzmjCxt+ObmDK1Kq42QE5pPju5kRM14jbUYjAI2BTNbvLqMsf9khvlqpQ2u7QLRS6qhqso/BYCfD/yLHTloAwLw1U5j+7kNsq+1ncXUqGWiwqx/EU/stFetW4an91upSEoZJyWWv/QzSA4v4dc3PALi45FGyUt3MXjGdYEtczmlQCUSDXR2x9xcv4rfjz2L6tbfx2/Fn8f5ri6wuKWE0OSZiN19xy4C7OXbSAlxpdfznkLuoqD2ZhRuusro8leA02NURab3yo6/+M/x7/8XcO/+gPffD1OQYjSGN9MAStvQKLXJ2WsEShhUs5tm1k9nhPsHiClUi02s+dUSqqyqxOYrCy/kCDMJmL6S6qlLnxB8GI1nsyXqFYEp0gF9Tdg8A6fZGK8pSSUJ77OqIRC9LAIdalkC1FbSdCGIDQKaHhl9y0muYevoNdM+ssrI0leA02NUR2bcsQWraCDIyB5OaNkKXJTgCWU0P4my6j/raSZEZMgA1vjzue3c2Oz3FB/lqpdqnQzHqiOmyBD+crWUn6YE38KbdwJZeTjLD2wXDut1DmL3iXu4beRm2lBZL61SJRXvs6gdx5Xbl+JMHa6gfoSZHOSl4SAv+K2p7bsYerv636WzaU8rLmy+3pjiVsDTYlbLQXvvptEguGYEXgf1j7QBn9n6JIcctZd6aKezyxv5ZrCp5abArZSVx4HOcS1rgTcQ0Ro21i8C1Q/6IIyXAU6uvt7hQlUh0jF0pi/kcFyCmCTFejHSJGmvv2mU30874NUU5X1hao0osGuxKWSxgL8NtP/CCfSd3/xSAYIudBr+T7PTajipNJSgdilEqHhiDvXk9YjwANNy85Lu7uWPp49y/fCYtRqyoUCUQDXal4oC9ZQN59WNID+xfznrCNWMifxcJ3Uxdu/vHvL7lIitKVAlEg12pOBBM6U8wpTcZ/hcj257LvinqmHP6zGdwz+U8ueomdjcc19ElqgSiwa5UPBDB5ygntfl9Ulp2H+gQJg+9HYBHProLCx5+phKEBrtScaLJMRGhhfTAK5Ft3x1r755ZxZWD/4taXx7uvfqoSNU+DXal4kTQ1o9ASn/SA69FbW891g4w5oTneHDMheSk13RkeSqBaLArFUfqujxCbeb/RG0buv2tqNcpYnDYAjT4s3hp02U6JKPa0GBXKo4EbX0xkhm17cZBi9s99r0d43hs5TTe/vKnHVGaSiAa7ErFmXT/C+Q0Xhe17btj7QDnHD+fAXmf8PjK3/FtY/eOKk8lADEWXMeJSDWwPcan7QbsifE5E5W2RTRtj2jaHtESqT2KjDF5hzrIkmA/GkTkE2PMgT+X3YloW0TT9oim7REtGdtDh2KUUirJaLArpVSSSaZgn2t1AXFE2yKatkc0bY9oSdceSTPGrpRSKiSZeuxKKaXQYFdKqaSTdMEuIjeJiBGRblbXYiUReUBENorIGhFZKCI5VtdkBREZKyKbRGSLiNxqdT1WEpECEVkqIhtEZJ2ITLG6JquJiE1EPhORl62uJZaSKthFpAA4B9hhdS1xYAlQYowZBGwGfmdxPR1ORGzAI8A4YAAwSUQGWFuVpYLAjcaY/sC/A5M7eXsATAE2WF1ErCVVsAMzgalAp78jbIx5wxgTDL/8EOhlZT0WGQpsMcZsNcb4gWeBiRbXZBljzC5jzMrw372EAi3f2qqsIyK9gHOBx6yuJdaSJthFpBz4yhiz2upa4tBVQPsrSSW3fKCy1euddOIga01EegOlwAprK7HULEIdwRarC4k1u9UFfB8i8ibQs51d04DfA6M7tiJrHaw9jDEvho+ZRugS/OmOrC1OtPfU505/NSciWcA/geuNCT89u5MRkQnAbmPMpyIywup6Yi2hgt0YM6q97SIyECgGVosIhIYdVorIUGPM1x1YYoc6UHvsIyJXABOAkaZzfmBhJ1DQ6nUvoMqiWuKCiDgIhfrTxpgFVtdjoWFAuYiMB9IBl4jMM8ZcZnFdMZGUH1ASkW1AmTEmUVZsizkRGQvMAM40xlRbXY8VRMRO6MbxSOAr4GPgEmPMOksLs4iEej3/C9QYY663up54Ee6x32SMmWB1LbGSNGPsqo2HASewRERWicgcqwvqaOGbx9cBrxO6Ufh8Zw31sGHA5cDZ4X8Tq8I9VpVkkrLHrpRSnZn22JVSKslosCulVJLRYFdKqSSjwa6UUklGg10ppZKMBrtSSiUZDXallEoy/w9SWpSRP3fDqwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 分别对多项式(MVM)和One-vs-Rest(OVR)进行Logistic回归\n",
    "for multi_class in ('multinomial', 'ovr'):\n",
    "    # 训练Logistic回归模型\n",
    "    clf = LogisticRegression(solver='sag', max_iter=100, random_state=42,\n",
    "                             multi_class=multi_class).fit(X, y)\n",
    "\n",
    "    # print the training scores\n",
    "    # 打印训练模型的性能\n",
    "    # print(\"training score : %.3f (%s)\" % (clf.score(X, y), multi_class))\n",
    "    print(\"训练模型的性能: %.3f (%s)\" % (clf.score(X, y), multi_class))\n",
    "    \n",
    "    # create a mesh to plot in\n",
    "    # 创建绘制图形的网格\n",
    "    # step size in the mesh\n",
    "    # 设置网格的间隔大小\n",
    "    h = .02\n",
    "    # 得到数据集的最大值和最小值\n",
    "    x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n",
    "    # 得到标签集的最大值和最小值\n",
    "    y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n",
    "    # 从小到大，间隔0.02创建坐标矩阵xx，yy\n",
    "    xx, yy = np.meshgrid(np.arange(x_min, x_max, h),\n",
    "                         np.arange(y_min, y_max, h))\n",
    "\n",
    "    # Plot the decision boundary. For that, we will assign a color to each point in the mesh [x_min, x_max]x[y_min, y_max].\n",
    "    # 绘制决策分界面，设定一种颜色一个分类\n",
    "    # 根据网格点，对数据进行分类预测\n",
    "    Z = clf.predict(np.c_[xx.ravel(), yy.ravel()])\n",
    "    # Put the result into a color plot\n",
    "    # 将结果变成一维向量\n",
    "    Z = Z.reshape(xx.shape)\n",
    "    # 初始化plt\n",
    "    plt.figure()\n",
    "    # 按照等高线进行绘制\n",
    "    plt.contourf(xx, yy, Z, cmap=plt.cm.Paired)\n",
    "    plt.title(\"Decision surface of LogisticRegression (%s)\" % multi_class)\n",
    "    # 设置坐标轴显示，tight:坐标轴数据显示更明细\n",
    "    plt.axis('tight')\n",
    "\n",
    "    # Plot also the training points\n",
    "    # 设置点的颜色序列为蓝、红、黄\n",
    "    colors = \"bry\"\n",
    "    # 绘制数据集X的散点图\n",
    "    for i, color in zip(clf.classes_, colors):\n",
    "        idx = np.where(y == i)\n",
    "        plt.scatter(X[idx, 0], X[idx, 1], c=color, cmap=plt.cm.Paired,\n",
    "                    edgecolor='black', s=20)\n",
    "\n",
    "    # Plot the three one-against-all classifiers\n",
    "    # 返回plt的参数范围\n",
    "    xmin, xmax = plt.xlim()\n",
    "    ymin, ymax = plt.ylim()\n",
    "    # 得到模型的w和b\n",
    "    coef = clf.coef_\n",
    "    intercept = clf.intercept_\n",
    "\n",
    "    # 定义绘制分隔超平面\n",
    "    def plot_hyperplane(c, color):\n",
    "        def line(x0):\n",
    "            return (-(x0 * coef[c, 0]) - intercept[c]) / coef[c, 1]\n",
    "        plt.plot([xmin, xmax], [line(xmin), line(xmax)],\n",
    "                 ls=\"--\", color=color)\n",
    "    \n",
    "    # 调用函数绘制分隔超平面\n",
    "    for i, color in zip(clf.classes_, colors):\n",
    "        plot_hyperplane(i, color)\n",
    "\n",
    "plt.show()"
   ]
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